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ABSTRACT. We study correlations in educational attainment across two and three generations in the US using linked data spanning 1940 to 2015. We find a 12 percent decline in the correlation of educational attainment over the 20th century. While we do find an economically meaningful “grandparent effect,” its magnitude is overstated due to mea- surement error. We also find evidence that the remaining grandparent effect is driven by the paternal grandfather for sons and the maternal grandfather for daughters. From our multigenerational results, we conclude that inferences derived using only two gen- erations of data understate persistence in educational attainment by 30 percent.

ABSTRACT. In evaluating economic performance of urban economies, some studies construct a single index score from multiple related measures of performance and use it for descriptive analysis. Others conduct multivariate analysis by regressing commonly-used performance measures such as employment and wage growth on a set of explanatory variables. This paper proposes an alternative approach by reducing GDP per capita, labor force participation rate, per capita personal income, and unemployment rate in 2004, 2006, 2009, and 2014 into a single principal component as the response variable for regression analysis. The results show that the share of population with at least a bachelor’s degree, the share of manufacturing employment, and establishments born per 10,000 persons contribute to better economic performance for U.S. metros in both 2004 and 2014. Nonetheless, further tests for the recent business cycle reveal that the aforementioned findings hold for 2006 but not for 2009, during which only the highly-educated share had a major influence on metro performance. This paper also examines how the same set of explanatory variables determines the growth performance from 2004 to 2014. The results show that the non-white population share is the sole variable fueling the decade growth in all models. Despite this, the low R-squared values in various growth models indicate that there is a need for further investigation into the growth mechanism.

ABSTRACT. The purpose of this paper is to discuss the need and propose a methodology for defining the boundaries between urban and rural when determining a study area in mid-sized metropolitan areas with no clear boundaries. Clearly defining study geographical boundaries of the study area is the the first important step in any empirical analysis. In many settings, it is important to delineate between urban and rural areas, due to the intrinsic difference in spatial patterns and processes occurring in these environments. Many conventionally used options such as jurisdictional, political, or Census boundaries have been used in the literature in the context of large metropolitan areas. However, for mid-sized cities, the urban or rural character of these lines can be ambiguous. As an example, county boundaries are overly imprecise to be practical. A typical mid-sized city truly operates as a region, incorporating parts of several inner or outer-ring suburbs into its functionality and day-to-day operability. How should the urban boundary of the metropolitan area be drawn? This paper suggests a geospatial approach to defining urban study areas of mid-sized metropolitan areas in a way that is both systematic and easily applicable to various spatial arrangements, so that resulting research can have maximum relevancy.

ABSTRACT. In recent months, the main cities of the Colombian Caribbean have been characterized by having the best figures in terms of unemployment. However, there are some aspects to improve in relation to the quality of the jobs oered. The objective of this paper is to analyze the main characteristics of the labor market of the three main cities of the continental Caribbean, namely, Barranquilla, Cartagena and Santa Marta. We emphasize the stylized facts related to labor informality and the quality of employment. The results show a decreasing evolution of informality in the Caribbean cities in the period 2007 until the first semester of 2018, however, Cartagena maintains 58.5% of its population in informal status, Barranquilla reaches a figure of 64% and Santa Marta reaches 66 %, while the main 23 metropolitan areas show a figure of 50.8 %. These aspects have repercussions on working life conditions, which we study in this work by means of the multidimensional index of quality of employment (IMCE). Regarding the latter, we found that the three cities have unattractive labor conditions in terms of quality of employment, which is more critical for the employed without any educational level, domestic workers or self-employed workers, and workers in small companies.

ABSTRACT. This paper examines the impacts of population aging on a wide range of economic outcomes from a regional perspective. Nowadays, many countries, including the United States, are experiencing population aging, which may have dramatic impacts on national and regional economies. Indeed, the size and composition of labor demand and labor supply are affected by population aging. However, there is little consensus of population aging’s impacts on local economies. This study uses regional variation of age structures to explain economic outcomes at the Metropolitan Statistical Areas (MSAs) level. Specifically: (1) Is there any association between the age structure and local economy? (2) Does age structure affect total economic growth, local labor market or people’s incomes? In order to identify causal effects, historical age structures and matching approaches are used to find suitable instrumental variables. This paper finds that regions with older-age structures tend to have larger growth rates of GDP per capita and slower growth rates of unemployment, but such positive effects are likely to fade away in the long run. Besides, no significant impacts of age structure on incomes are found. The results are robust before, during and after the economic recession. Quantile regressions are also used to explore the heterogeneous effects among MSAs, but the results show that MSAs, regardless of their sizes, are uniformly affected by age structures.

ABSTRACT. The dramatic increase in drug overdose deaths (OD) has led to an increase in midlife mortality rates in the United States. The drug crisis has implications across society for economics, health, and families. This study seeks to understand how opioid overdose rates are related to marriage behaviors and how these relationships might differ among men (vs women) and across levels of educational attainment. Marriage is impactful on individual subjective well-being, child outcomes, and economic conditions; by understanding the relationship between opioids and marriage behaviors we will better understand the broader impacts of drug use on American society. Based on our literature review, we hypothesize that higher county-level OD rates will be associated with decreased likelihood to marry in a given year; we further expect these results to be more pronounced for those with a high school education or less and for males.

We combine county-level mortality data from the National Center of Health Statistics (NCHS) with individual level American Community Survey (ACS) data from 2008-2016. Our predictor variable is poisoning deaths per 100,000 individuals taken from the NCHS. The outcome variable of interest measures whether an individual was married within the last year, calculated from the ACS. The ACS provides the remaining demographic and control variables. Using the marriage outcome variable of interest, preliminary analysis shows an increase in local overdose rates is related to decreases in the probability that an individual will marry within a given year. Our results also indicate that this marriage suppression holds with annual differencing for two and three year periods. Our findings support previous assertions that there are sex and education differences in marriage behavior; our analysis indicates that opioid poisoning rates are associated with marriage independent of these factors.

ABSTRACT. The State of West Virginia has the highest rate of drug overdose deaths in the nation and has seen an 80% increase in the overdose death rate since 2010 and a 350% increase since 2001. In addition to the social and economic impacts associated with drug overdose deaths, West Virginia also exhibits other public health issues that accompany widespread illicit drug use, such as an infection rate of hepatitis B that is fifteen times that of the national average. With these important public health issues in mind, in this paper we utilize individual-level death certificate data for the state of West Virginia from 2001 to 2016 to identify factors contributing to the likelihood of an individual dying from a drug overdose. This micro-level analysis allows us to link individual deaths to local socioeconomic, industry, and housing data over the same time period. This allows us to gain some insight about the impact of regional economic decline—such as that observed in southern West Virginia’s “coal country”—on drug overdose deaths, as well as control for a variety of other socioeconomic characteristics specific to the individual’s area of residence. We can also examine how these factors may be contributing to the non-uniform impact of opioids across age and gender groups, as well as the heterogeneous geographic distribution of overdose deaths across the State.

ABSTRACT. Deaths from opioid-use disorders (OUDs) have become a major drug issue in the United States. OUD deaths have risen by 430 percent since 1999; and today nearly 70 percent of drug overdose deaths involve opioids (CDC 2018). However, mortality has increased at a much faster pace in rural versus urban areas, increasing by 185 percent in large central metro areas, 693 percent in micropolitans, and 725 percent in noncore/rural areas (CDC 2017). Further, the crisis is in constant flux as the type of opioids have changed. The so-called first wave included prescription opioids starting in the late 1990s, followed by heroin second wave in 2010, and the current third wave that include synthetic opioids and mixes of all three drugs. Our analysis seeks to identify OUD mortality clusters by type of drug at the county level; and to describe the socioeconomic and spatial correlates of these clusters. Using restricted mortality data from NCHS-CDC from 1999 to 2016 for counties in the contiguous U.S., we employ latent profile analysis to class counties into unique OUD mixtures using Bayes posterior probabilities. We then model membership in these classes using multinomial logistic regression with socioeconomic correlates taken from secondary data sources. We identify several epidemic clusters (prescription opioids, heroin, and emerging heroin) and two syndemic clusters involving multiple opioids. Regression analysis suggests certain classes are driven by four trajectories: the rural left behind, polarized large cities, declining micropolitans, and suburban drug use.

ABSTRACT. This paper aims at measuring the effects of oil and gas development on a state’s opioid overdose death rates. We estimate a spatial panel model to account for spatial spillovers and spatial and time fixed effects. To account for mining, oil, and gas development we follow the work of Rajbhandari (2017) and estimate proxies for change in percentage of the sectoral employment over time. Our results point towards an effective decrease in death rates in times of boom and increases in times of bust. The spatial spillovers show a positive (higher death rate) spillover effect for the neighboring states. The policy variables have statistically significant effects on death rates.

ABSTRACT. Value-added activities associated with food processing are increasingly a revenue source for farm business and farm family households. Even though consolidation in national food brands persists, larger food retailers seek to integrate popular local food producers and products into their store formats due to renewed consumer interest in local and regional food brands. The rise of a bimodal food manufacturing structure with both, a stable set of large, national players, but also a small and dynamic set of firms more regionally dispersed across the U.S. may, in essence, be mimicking the steep rise in microbreweries over the past 30 years (New York Times, February 27, 2018). Moreover, a similar restructuring may also emerge in food distribution and retailing sectors if market intermediation and access need to better fit the segmentation of products, brands and types of food buyers (Conroy et al., 2015). While overall food and beverage spending is stagnant, there has been a shift in consumer spending to smaller and private brand manufacturing. Consumers have an unprecedented ability to access information about products and share this information via social media, creating an imperative for manufacturers to reset and reposition themselves with consumers and shoppers (Deloitte, 2018). Our prior work identifies the changing prevalence of small and new establishments in parts of the food manufacturing sector, likely driven by increased entrepreneurship in food supply chains. For example, bakeries exhibit reverse consolidation or the emergence of small- to mid-sized plants with increasing geographic scope or relocalization. This paper seeks to better understand how place-based factors influence the location decisions of food manufacturing plants and also how these factors are associated with employment at these plants. There has been much research in this area, but not at the establishment level. Prior research finds that rural areas are at a comparative disadvantage with respect to attracting demand-oriented food processors, but non-metro counties with ties to urban centers may be attractive investment sites to supply-oriented food manufacturers (Lambert et al. 2006). The ability of rural counties to attract food manufacturers to create local employment opportunities and market outlets for farmers varies considerably across subindustries and little research has been done recently to identify whether determinants of food industry location decisions have changed (Goetz, 1997). One forthcoming paper by Cleary et al. does find that the presence of direct sales, complementary food establishments, and higher social capital proxies lowered the “population threshold” necessary to support a locally-focused food distributor appearing in a county (following Bresnahan and Reis’ 1991 seminal work). This work seeks to explore the same geographical dimensions of food manufacturing location decisions.

ABSTRACT. “Cottage food” laws have been developed to help small businesses that produce non-hazardous foods lower perceived barriers to entry, and more recently, to adapt to stringent food safety requirements. Cottage food laws have been passed in many states in the U.S., particularly within the past ten years. While the details of how the laws are implemented vary at the state-level (and in select states at the county-level), in general the regulations allow home bakers to produce goods in their own kitchen and market them at direct-to-consumer (DTC) outlets like farmers markets, fairs, and at catered events. In some states sales to retailers are allowed provided total sales are below a threshold. The types of foods allowed under these laws typically include baked goods like bread and cookies; sugary products like candy; canned, pickled, or dried fruits and vegetables; and other snack foods. As conceptualized, the laws are intended to help entrepreneurial food business get started and, after gaining experience, increase to a larger scale with more rigorous health department inspections. Despite the large interest in these laws, only a few case studies of cottage food laws exist in the literature. There has been little to no national-level evaluation of cottage food laws. One impediment in evaluating cottage food laws is that DTC sales data tracked in the Census of Agriculture is only collected from farmers for unprocessed commodities. Thus, value-added product sales are excluded. Nonetheless, many federal grant and loan programs (e.g., Farmers Market Promotion Program, Local Food Promotion Program, and Value-Added Producer Grants) have been used to assist food entrepreneurs with marketing products through DTC channels. Thus, understanding how small businesses can be impacted through developing DTC and other direct-retail market channels would be highly valuable in informing how to target technical assistance resources effectively. In examining food industry trends, the food manufacturing sectors that experienced the greatest increase in the number of establishments in the past decade are for non-hazardous products: chocolate, baked goods, coffee/tea products, and processed fruits and vegetables. Further, the two sectors that experienced the greatest declines were for two sectors ineligible for cottage food laws: animal and seafood processing. In addition, for baked products, the states that experienced the greatest increase in establishments were states that passed cottage food laws. We propose to use the National Establishment Time-Series (NETS) database to compare the performances of small food production businesses impacted by cottage food laws to those that are unaffected. We propose to estimate a state-level difference-in-difference model between 1990 and 2015 using twenty NAICS food manufacturing sectors measured at the 5-digit level. Our dependent variable will be a variable like establishment/firm counts or employment. We will also track how newer businesses performed, their growth rates, and the turnover in businesses. The main independent variable of interest is a dummy variable that switches from 0 to 1 when a state passes a cottage food law for a food manufacturing sector. The dummy only switches from 0 to 1 for sectors affected by the law. We will control for state, year, and sector effects using indicator variables. We could further include controls for state-level macroeconomic trends like changes in personal income, demographic issues, and changes in the structure of other sectors in the economy. We also plan on performing a variety of sensitivity analysis since the details of cottage food laws vary by state. For instance, some states have restrictive caps on sales levels for such production, while in other states sales are unrestricted. Also, in some states numerous laws have been passed incrementally over time.

ABSTRACT. This paper will highlight the use of a Colorado-based community engagement process to frame the contributions and opportunities in the food system as a means to catalyze new interdisciplinary research. Given the current market, supply chain and policy environment facing Colorado's ag and food enterprises, this paper will highlight a portfolio of case studies and methods to explore tradeoffs policy makers and managers might consider.

ABSTRACT. After the economic shock of the Great Recession in 2007-2008, the Appalachian Regional Commission (ARC), began exploring different resources to rebuild and strengthen local economies. Economic resilience identifies how a region is impacted from economic shocks, as well as how they recover. We examine the effects of ARC grant project investments from 1966 to 2006 on economic resilience to the 2007-2009 Great Recession. In this analysis, economic resilience is measured by the changes in local employment levels. We utilize economic control variables as measured before the economic shock to predict county-level economic resilience to the Great Recession.

Based on the results of our analysis, we can make three major conclusions from this study. First, we identify socioeconomic characteristics that could promote or restrict local economic resilience. This article contributes to the literature by investigating the effects of ARC grant project investments on local economic resilience in the greater Appalachian region. We hypothesize that federal support will increase stability, making communities more resilient to economic shocks. Furthermore, we can recommend policy strategies to enhance economic resilience throughout the region. Socioeconomic characteristics that influence a region’s economic resilience could infer local or regional policy strategies. When making policy recommendations one must take into consideration the spillover effects beyond the county where the policy may be implemented. Therefore, we utilize spatial econometric techniques to control for these neighboring (spillover) effects. Last, we can identify which counties are performing at high levels of economic resilience. These counties should be examined as case studies to identified localized strategies for resilience.

ABSTRACT. Regional economic resilience is often considered in terms of employment returning to peak and recovering back to the historical trend of economic growth. In this way, resilience can be understood as ‘hysteresis,’ that is, how regional economies respond to recessionary shocks. The Great Recession, for example, can be seen as a nation-wide shock that temporarily disrupts a region’s economic growth. Researchers have proposed measures for this type of shock resilience, namely, the extent of the shock (drop in employment from peak), the duration of the return (time for returning to peak employment at the beginning of the recession), and the recovery to the expected level of employment based on the historical employment trend for a region. This scenario of drop, return and recovery to trend has a foundation based in robust theory, as presented by Martin (2012), among others, and can be described as a resistance to a shock – minimal drop – and quickness or capability to recover. The plot of the exemplar regional scenario is not unlike the national aggregate experience of an economic downturn like the Great Recession. The exemplar scenario, however, and the simple elegant graph of drop, return and recovery to trend are products of survivorship bias. A mere 588 of 3100 U.S. counties had returned to their 2007 pre-recessionary employment peak as of 2011. As of 2016, 1797 counties had not returned to their 2007 employment peak; these are not the survivors that are typically the focus on attention. Nearly a quarter of U.S. counties – 754 – are experiencing a secular decline in employment, making it difficult to measure the extent of, and year of, the return of peak employment. It also challenges the definition of resilience. Is resilience an internal condition that manifests itself when perturbed by a national economic cycle? Is regional resilience contingent upon neighboring regions? What of exogenous, non-cyclical shocks, like corporate headquarter’s decision to move production out of a region or site a new plant in the region? Is it legitimate to include sector specific shocks – positive or negative – that arise from changes in international commodity prices, like oil, iron ore or soybeans? In this paper we conduct a first order approximation of industry re-configuring, or industrial structural evolution, over time by U.S. county to determine whether a one-size-fits-all measure of drop and return resilience may present a false signal of a region’s resilience. That is, the region may simply been lucky to have benefited from an oil and gas boom or a salient investment in a new auto plant rather than having an ability to absorb an economic shock or quickly bounce back from a dip in the national economic cycle. A booming oil and gas sector in a region may mask the deeper economic decay in evidence in other sectors. In this paper we decompose the time series data of county employment from 2002 to 2016 into twelve industry super-clusters (or sectors) to determine if there is a relationship between changing industry shares and two measures of resilience, one of our own design and the other of Han and Goetz (2015). We find that employment in the shock-prone sector consisting of natural resource industries and the business services and support sector have a positive relationship with our measure of resilience, while all other sectors have a generally negative or statistically insignificant relationship. The latter sector appears to provide a true signal of a region’s resiliency employment context, one for which the business services is able to absorb labor that is made redundant in other sectors during a recession. The authors also suggest that regions experiencing secular declines in employment may be either smart shrinkage resilient – in which case the region’s industries are able to absorb some of the redundant labor -- or distressed. The latter describes a region for which most regional industries are losing jobs and no sector shows signs of absorbing redundant labor. New measures for shrinkage are suggested.

ABSTRACT. Background The world’s climate is changing noticeably in recent past and one of the impacts is the increase in the occurrence and severity of climate related disasters. Some natural disasters are common to almost all geographic areas but some are more specific to certain region and seasonal. The losses caused by disasters are likely to disrupt the development of the affected communities and deteriorate the wellbeing of the affected population. Even with the current state-of-the-art technology, we cannot predict the exact time and nature of disaster well in advance. Despite of the existing knowledge about the spatial distribution of natural disasters, preference for certain amenities and opportunities has attracted people to move to some localities that are naturally disaster-prone like coastal belt, and this aggravates the exposure to disasters. Therefore, mitigation, preparedness and recovery actions are very important in the efficient management of disaster and for the reduction of community vulnerability. It is generally believed that communities with better disaster preparedness have more disaster resilience and show quick recovery from the disaster induced losses. The vital question that the government and local communities face in the disaster management issues is- what makes the community more resilient against climate related disasters in terms of socio-economy and ecology. Despite the recent efforts by researchers (Han and Goetz, 2015; Kim and Marcouiller, 2015), there still exists gaps in the understanding of characteristics of the economies that contributes to resilience building. This paper contributes to that literature by exploring factors that enhance adaptive capacity of a community by focusing on the labor market. Regional economic resilience is defined as a region’s capacity to absorb and resist shocks as well as to recover from them (Han and Goetz, 2015). Community resilience is often associated with the capacity of a community to cope with disasters and therefore, adaptation behavior involved in the process of recovery is crucial. The relevant literature indicates several forms of capital, like economic, human, social, physical and natural capital that contribute to resilience (Mayunga, 2007). Different forms of capital create different kind of opportunities which include knowledge, skill, wealth, social network and etc. There are previous attempts to construct an objective community resilience index which did not address two concerns satisfactorily; first, what components should be included in formulation of index and second, how to assign weight to the components. This paper contributes in the following ways: 1) quantitatively explores the role of social, human and economic capital in community resilience, 2) considers the regional labor market as a whole, not any specific sector, and 3) controls for the industry composition of that economy.

Data and method Using the US county level annual disaster data from 1990 to 2015 and fixed effect model, this paper examines factors contributing to the community resilience in the face of climate related disaster by focusing on two dependent variables- per capita wage and number of employment. The basic relationship of interest is as follows: y_it = α_1*D_it + α_2*X_(it-1) + α_3*D_it*X_(it-1) + α_4*N_it + α_5*C_it + α_6*Z_(it-1) + λ_i + γ_t + ε_it … (1) In this paper, we have considered three climate related disasters– flood, extreme heat and storm. D_it is a dummy variable indicating whether a specific type of climate related disaster occurs in county i and year t. X_it includes controls for the human capital, social capital and industry share at county level. The proportion of population with a college degree is included as a proxy of human capital. Number of social organization is included as social capital proxy. Vector N_it includes control for spatial and temporal effect of disasters. It includes a dummy variable that indicates climate-related disasters in any of the neighboring counties of county i in year t. It also includes dummy variables that indicate past disaster incidents in the county i and in any of its neighboring counties. C_it includes the mean temperature, total precipitation and their squared terms. Z_it includes county-specific demographic variables, like gender, race and age that may affect local labor market. λ_i and γ_t capture the spatial fixed effect and time fixed effect, respectively and ε_it is the error term. The interaction terms with X_it are included to measure the effect of socio-economic variables conditioning on the disaster occurrence. Our main interest lies in the parameter dy/dX|(D_it=1) = α_3. Communities with different socio-economic conditions, human and social capital and industry composition is expected to show different adaptive behavior when disaster strikes. This term is expected to capture that effect. As a robustness check, we include the interaction of disaster with quadratic terms of socio-economic variables to control for possible nonlinearity. The results are qualitatively unchanged.

Results and discussion The preliminary results show that various climate related disasters affect the local labor market differently. We analyze the marginal effect of several control variables conditioning on the disaster occurrence. We find that economies with highly concentrated industries performs poorly in the face of climate related disasters. This finding is very relevant for the rural communities that have higher dependence on agriculture. Social capital also plays a positive role in the adaptive behavior of the community that indicates that networking and social norms may contribute in the disaster related adaptation process. However, the preliminary results also indicate that communities with more college graduates face negative impact in the labor market following a disaster which is counter intuitive. When considered along with industry concentration, role of human capital in the community adaptive behavior is very significant. Identifying the factors that help to build a disaster resilient community contributes in the effective planning of disaster management, and enables the efficient use of resources to ensure the future sustainability of the disaster-prone communities. This paper is an effort to understand the underlying mechanism of community adaption process in response to disasters and the use of this approach may extend to measure community resilience against other exogenous economic shocks.

References Han, Y. and Goetz, S.J., 2015. The economic resilience of US counties during the Great Recession. The Review of Regional Studies, 45(2), p.131. Kim, H. and Marcouiller, D.W., 2015. Considering disaster vulnerability and resiliency: the case of hurricane effects on tourism-based economies. The Annals of Regional Science, 54(3), p.945-971. Mayunga, J.S., 2007. Understanding and applying the concept of community disaster resilience: a capital-based approach. Summer academy for social vulnerability and resilience building, 1, p.16

ABSTRACT. The Great Recession has created substantial interest in local resilience to economic shocks. However, economic resilience is a nuanced concept with multiple definitions of response to a shock including returning to a previous growth path, engineering resilience, stability through a shock, ecological resilience, or restructuring to a new growth path, adaptive resilience (Martin & Sunley, 2015). Therefore, tension remains between translating this multidimensional concept into a measure. Among the available resilience metrics, Lewin, Watson and Brown, 2018 measure the likelihood of entering a recession and Ringwood, Watson and Lewin, 2018 measure the depth of job loss and net out expected business cycle changes. Most recently, Han and Goetz (2018) extended their 2015 definition to better account for the duration of a drop and speed of recovery by modeling it as an impulse.

This research expands upon Han and Goetz (2018) to account for trade partners and neighbors spillover effect on the duration of the drop and the recovery. Using U.S. county employment data, we apply a spatial model incorporating inter-county trade balances to examine the impact of county economic interdependencies on resilience in the presence of an economic shock – the financial crisis that leads to the Great Recession. We conduct a robustness check by modeling these spatial effects across recent reconstructed measures of resilience.

Fewer papers have integrated the influence of other counties. Previous research has considered the spatial spillover effects of a neighboring county’s economic diversity on both county unemployment (Watson and Deller, 2017) as well as stability among other economic measures (Deller and Watson, 2016). This work supported diversity as a stabilizing influence for unemployment rates. Han and Goetz (2018) use I-O models to calculate three national centrality measures that they downscale to the county level using a weighted average of local employment across selected industries. Their findings suggest that industry centrality, in particular industry strength, influences resilience to shocks at the local level. Han and Goetz and others incorporate county characteristics such as migration and commuting to reflect the connectivity of local economies, however the spatial interactions between counties and their effects on resilience has remained largely unexamined.

References: Deller, S., & Watson, P. (2016). Spatial variations in the relationship between economic diversity and stability. Applied Economics Letters, 23(7), 520-525.

Han, Y., & Goetz, S. J. (2018). Predicting US county economic resilience from industry input-output accounts. Applied Economics, 1-10. https://doi.org/10.1080/00036846.2018.1539806

Han, Y., & Goetz, S. J. (2015). The economic resilience of US counties during the Great Recession. The Review of Regional Studies, 45(2), 131.

Lewin, P. A., Watson, P., & Brown, A. (2018). Surviving the Great Recession: the influence of income inequality in US urban counties. Regional Studies, 52(6), 781-792. https://doi.org/10.1080/00343404.2017.1305492

Martin, R., & Sunley, P. (2015). On the notion of regional economic resilience: conceptualization and explanation. Journal of Economic Geography, 15(1), 1-42. https://doi.org/10.1093/jeg/lbu015

Ringwood, L., Watson, P., & Lewin, P. (2018). A quantitative method for measuring regional economic resilience to the great recession. Growth and Change. https://doi.org/10.1111/grow.12265

Watson, P., & Deller, S. (2017). Economic diversity, unemployment and the Great Recession. The Quarterly Review of Economics and Finance, 64, 1-11.

ABSTRACT. While technology-induced urban inequality has been attracting great attention from scholars and policymakers, the literature of skill-biased technical change has been silent regarding the two key channels, namely migratory and demand of education, through which technology increase spatial inequality. In this study, we empirically identify these two channels through which innovation can affect skill distributions across urban counties in the United States. The study of these channels are important from academic and policy standpoints. Instrumental variables estimations show that educational channel on play greater role than migratory channel between 2005 and 2015 which corresponds to the decade of low migration rate in the United States. Using patents as a novel measure of skill-biased technical change, this paper can shed light on the relationship between technological progress and urban inequality from a new angle. Additionally, we also examine the impacts of innovation on wealth inequality across urban areas. Specifically, using patent data, we are able to investigate the close and positive relationships between computer and data processing, telecommunications, automation and urban wealth disparity.

ABSTRACT. Broadband adoption is primarily measured as the percentage of a population with a connection, regardless of the modality used (i.e. fixed, mobile, or both). This results in a binary measurement that distinguishes between two groups: the percentage that have the defined level of access and those that do not. However, this measure fails to capture differences that may exists in how users connect, for example, those who use both mobile and fixed versus those who use mobile only. A wide array of studies have built the case that broadband adoption – traditionally defined as a fixed, wired connection – can positively affect households and communities.

This article proposes the use of the absolute value index (AVI) as a measure to study broadband adoption inequality. Using nationally representative data, adoption is broken into four types of connections(none, mobile, fixed, both) to compile the AVI. This measure of inequality may better represent the disparities associated with broadband use across the country, particularly as mobile internet use rises. The results indicate that the AVI can be useful in differentiating adoption patterns (i.e. mobile vs. fixed) in states with similar aggregate levels of adoption. However, two non-nested hypothesis tests formally explore the explanatory power of the two measures in explaining economic relationships commonly associated with broadband adoption, and conclude that the AVI does not capture any additional information about the economic state of the area it is measuring.

ABSTRACT. This paper analyses the long-term relationship between regional inequality and economic development. Our data set includes information on national and regional per-capita GDP for four countries: France, Italy, Portugal and Spain. Data are compiled on a decadal basis for the period 1860-2010, thus enabling the evolution of regional inequalities throughout the whole process of economic development to be examined. Using parametric and semiparametric regressions, our results confirm the rise and fall of regional inequalities over time, i.e. the existence of an inverted U curve since the early stages of modern economic growth, as the Williamson hypothesis suggests. We also find evidence that, in recent decades, regional inequalities have been on the rise again. As a result, the long-term relationship between national economic development and spatial inequalities describes an elephant-shaped curve.

ABSTRACT. On December 12, 2018, the U.S. Bureau of Economic Analysis released prototype measures of gross domestic product (GDP) by county. While other measures of county economies rely mainly on labor market data, these statistics are the first of their kind in that they incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the output of capital-intensive industries is captured more accurately than prior methods based solely on labor market data. The new county-level GDP statistics will assist economic analysts’ efforts to gauge the performance of local economies and policymakers developing strategies to promote economic growth. They will also help answer important questions related to the size and condition of local area economies, industrial composition, and comparative growth trends. These statistics represent another step forward in meeting BEA's long-standing goal of providing a more detailed and accurate geographic distribution of the nation's economic activity.

ABSTRACT. Historically, residential housing services or “space rent” for owner-occupied housing has made up a substantial portion (approximately 10%) of U.S. GDP final expenditures. The current methods and imputations for this estimate employed by the Bureau of Economic Analysis (BEA) rely primarily on designed survey data from the Census Bureau. In this study, we develop new, proof-of-concept estimates valuing housing services based on a user cost approach, utilizing detailed microdata from Zillow (ZTRAX), a “big data” set that contains detailed information on hundreds of millions of market transactions. Methodologically, this kind of data allows us to incorporate actual market prices into the estimates more directly for property-level hedonic imputations, providing an example for statistical agencies to consider as they improve the national accounts by incorporating additional big data sources. Further, we are able to include other property-level information into the estimates, reducing potential measurement error associated with aggregation of markets that vary extensively by region and locality. Finally, we compare our estimates to the corresponding series of BEA statistics, which are based on a rental-equivalence method. Because the user-cost approach depends more on the market prices of homes, we find that since 2001 our initial results track aggregate home price indices more closely than the current estimates.

ABSTRACT. Empirical models of regional adjustment are used to answer a variety of questions in urban, regional and labor economics. These models often include variables that are highly persistent, such as regional unemployment rates. Whether such variables are modelled as mean-reverting or non-stationary in the empirical specification can lead to substantially different conclusions regarding how regional economies absorb and recover from economic shocks. To address this problem, we apply a recently-developed model-averaging method to a set of regional adjustment models in the tradition of Blanchard and Katz (1992) to assess the impact of regional shocks on local population, employment and unemployment in US cities. The set of candidate models span both stationary and non-stationary specifications of regional unemployment rates. Our results suggest that regional adjustment is highly protracted, firm-mediated, and partial–meaning that regional downturns have a permanent effect on local unemployment rates.

ABSTRACT. Regional wage disparities in the United States have been a topic of research for decades (Segal 1961; Roback 1982; Krugman 1991; Partridge et al. 2015) and policy makers often develop strategies with the intent of raising wages in their region. These strategies, however, are hampered by a monolithic understanding of how wage differences can arise. While there are countless reasons for why average wages vary by region, a fundamental deductive distinction can be made between regions that are concentrated in higher than average paying sectors (i.e. an above average paying industry mix) and regions that pay above the national average wages for their respective industry mix. Therefore, two disparate regions may have the same average wage for two very different reasons; region 1 may have a relatively low paying industry mix, but they pay above average wages for those relatively low paying sectors and region 2 may have an industry mix that is concentrated in relatively high paying sectors, however those sectors in the region pay below the national average for the respective sector. Even though the two hypothetical regions may have the same overall average wage, the underlying structure of the region’s economies are likely very different. Similarly, a region’s low average wage could arise from these two very disparate structural problems to varying degrees. Furthermore, the policy prescriptions for the economic development of a given region are likely very different for regions which possess a relatively low paying industry mix than for regions with a relatively high paying mix of industries, but for which the wages paid in the region are bellow national average wages for that region. This analysis starts with developing a deductive wage decomposition methodology which splits the difference in the region’s wage to the national wage into a “wage effect’, “industry mix effect”, and “interaction effect”. This decomposition shares some similarity to a shift-share analysis (Stevens and Moore 1980) for wages, however, the decomposition developed here is fundamentally different from shift-share analysis and does not trivially reduce to a shift-share. In decomposing the difference in any given region’s wages to the national average into these three components which perfectly identify the wage differences, the specific reasons for why a region’s wages differ from the national average can be more elegantly diagnosed. Results of the regression model indicate that factors such as income inequality, percent union participation, and educational attainment affect the components of the wage differential decomposition very differently.

ABSTRACT. Most previous studies investigate the impacts of offshoring only on a negative effect. They conclude that offshoring reduces employment and wage of American workers. This negative effect is known as displacement effect or the effect that directly affects labor market. Recently, however, some studies propose that offshoring could have a positive impact on labor market. They find that offshoring increases workers’ productivity, research and development, and firms’ outputs. Consequently, employment and wage may increase from the output and productivity expansion. They call it as output effect which could be another factor that creates positive benefit of offshoring to workers indirectly. This paper, therefore, studies the total impacts of both displacement effect and output effect at a county level in the United States. We find that overall offshoring has a significantly positive output effect, but has no direct significant impact on employment. This leads offshoring to have a positive total impact on domestic employment through output expansion. Moreover, this study also considers on offshoring across sectors which we call spillover effect. The result shows that cross-sectoral offshoring of service sector decreases domestic employment in manufacturing significantly. On the contrary, cross-sectoral offshoring of manufacturing increases domestic outputs in service sector.

ABSTRACT.

The objective of the research was to understand the migration decisions by answering two questions; (1) who experiences more friction in spatial mobility? (2) how does perceived distance influences migration? By utilizing three types of informational fields, individual’s migration decisions were classified into four types of discrete movements; (1) no move or movement within the same commuting zone (2) movement within the same trade area, but to different commuting zones (3) movement within the same Census region, but to different trade areas (4) movement to other Census regions. I used a multinomial logit model and 2016 1-year ACS PUMS data in the analysis. I found that individual and household factors experience different friction in spatial mobility. Also, our result suggests that in the hierarchically “longer” migration, the influences of labor market and amenities factors decline.

ABSTRACT. Especially devout adherents to religious belief systems containing an afterlife component - highly confident that an afterlife exists after death - may worry less about death and, thus, make more risky occupational choices than non-believers or individuals with weaker afterlife beliefs. This study attempts to test the role that an individual's afterlife belief strength may play on that person's choice of occupation. In the first part of the analysis, occupational risk data from the National Institutes for Occupational Safety and Health (NIOSH) is combined with micro-level data from the 1998 General Social Survey (GSS); the GSS data, in addition to the usual controls, includes religious information on the household head. Additional analysis utilizes county level data to provide an extension at the regional level with respect to occupational distributions.

ABSTRACT. The divergence in housing price growth in the U.S. in coastal cities relative to inland cities has been thought to occur, in large part, due to severe housing regulations and restrictions on development. Researchers have posited that this trend implies that these heavily regulated cities are experiencing higher incidences of gentrification. However, the gentrification of lower income communities may be negatively influenced by restrictive regulations rather than positively, as is the case with overall housing price growth. This will occur if restrictions make it more difficult to improve housing structure and engage in new housing projects. We use data from 30,000 census tracts to analyze the influence of land use regulations and restrictions on the probability an area will undergo gentrification in the years 2000 to 2010. By separating the effects of higher levels of regulation on overall housing price growth from the likelihood that a lower-income neighborhood will gentrify, we find that regulation has opposing influences. Increased levels of regulation are indeed associated with higher overall housing prices but are also associated with a 3-4% reduced probability that a tract will gentrify, contrary to previous conclusions.

ABSTRACT. This paper provides new evidence on the effect of homeownership on unemployment spells by disaggregating exit from unemployment into full-time and part-time employment using the March Current Population Survey (CPS) data from 1990 to 2013. Using duration models, we find that when transition from unemployment to different types of employment is ignored, homeownership decreases the exit rate from unemployment. However, when the transition to different types of employment is considered, homeowners have lower rates of exit into full-time employment than renters but have higher rates of exit into part-time employment. Estimates from a competing risks model which simultaneously models the transition into full-time and part-time employments are similar. These results are robust to different specifications.

ABSTRACT. From 1999 to 2005 the Spanish housing market was characterised by an extraordinary boom, which increases house prices (euros per m2) by 117%. This housing bubble had a crucial role on the impact of the international financial crisis beginning in 2008 in the Spanish economy. After 2008, during the Great Recession, house prices dramatically decreased and unemployment increased. At the same time, the number of defaults on the repayment of mortgage loans and foreclosures significantly raised. In this paper, we examine the effect of the Spanish law reform passed in 2012 to protect mortgage debtors. Under this new regime, low-income debtors that meet some requirements can hardly be evicted and, in case of default, the bank is forced to offer the debtor a restructuring of the debt or even, as a last resort, the debtor can deed the property over to the bank as an alternative to having the lender foreclose on the property. We consider data from 50 Spanish provinces (NUTS III regions) from 2001 to 2017. By using panel data models with fixed effects, linear and quadratic region-specific time trends and other relevant control variables at the regional level (house prices, inflation and unemployment rates), our results reveal that the reform had a significant effect, reducing the number of foreclosures and new mortgage loans, but this effect was transitory, fading after four years.

ABSTRACT. Each year, agriculture plays a major role in bolstering Arkansas’ economy. In 2016, Arkansas’ aggregate agriculture sector contributed $20.2 billion in value added, equaling 16.3% of the state’s total value added. That same year, economic activity spurred by Arkansas’ agriculture sector also played a role in upholding 266,591 jobs, while generating $9.9 million in wages, and $12.3 million in total labor income. In addition to evaluating the annual economic contributions of agriculture, it is important to understand how these values change over time. In this study, trends in agriculture’s economic contributions to the state of Arkansas are analyzed over a fifteen-year period from 2001 to 2016. Trends analyzed include direct industry output, exports, employment contributions, and value added contributions. Relative contributions of crops sectors, animal sectors, and forestry sectors are compared over time. Results of the analysis highlight the role that agriculture has played over time in maintaining the stability and sustainability of the state’s economy through both direct economic contributions, and value generated through interactions with other industries.

ABSTRACT. The American Alligator is the official state reptile in the States of Florida, Louisiana, and Mississippi. With nearly 7 million acres of suitable habitat statewide, Florida is home to an estimated 1.25 million alligators, over 20% of the overall population. Although the alligator has become synonymous with the state, the value of the economic activity associated with the alligators has not been measured. Activities such as farming, meat and hide processing, hunting, and wildlife tourism all contribute to the regional economy. This analysis combines data on alligator farms, hunting revenues, and meat and hide production from the Florida Fish and Wildlife Conservation Commission, estimates of state park attendance data from the Florida Department of Environmental Protection, and input-output data for the State of Florida available from IMPLAN to measure the total economic contributions of the American Alligator to the State of Florida in 2016. Analyses of this type capture not only the direct economic activity within these industries, but the indirect activity supported throughout the regional economy via supply chain relationships and the re-spending of household income. The study also discusses the potential pitfalls of choosing different economic contribution methods.

ABSTRACT. Rural development continues to evolve and the rural wealth creation (RWC) framework has become an increasingly appealing way of approaching complex development challenges. The framework aims to reduce inequality and poverty through a locally led and context specific process that measures progress through the community capital framework. RWC has broad appeal as a rural development tool because of a multifaceted approach that is responsive to a wide range of contexts: it is entrepreneurial and innovative, locally driven, asset and market based, a systems approach that uses value chains, and it considers the broader impacts of a development decision with the community capitals framework (Pender et al., 2014).

RWC has been adapted into a strategic planning effort to guide development and build wealth through coordinated value chain efforts in the WealthWorks approach (Ratner and Markley, 2014 and Lyons and Wyckoff, 2014). This systems thinking approach is still nascent. Research and practice continue to explore implementing the feasibility of a complex systems-approach to development in rural areas and the necessary skills for effective value chain coordination with different market access and different internal capacity for coordination and management (Lyons and Wyckoff, 2014).

On-going work is examining how to empirically measure multiple forms of capital (Schmit et al., 2017; Johnson, Raines and Pender, 2014; Pender et al., 2012b). More work remains to understand and improve implementation of these concepts, especially how to leverage investments in value chains (Ratner and Markley, 2014) and how investing in one form of wealth can build other forms of wealth (Pigg et al., 2013 and Schmit et al., 2017). As Pender et al., 2012a note there is a need for “more research on what works where and why.” This research contributes to this gap in the literature by providing case studies of intentional efforts to support rural entrepreneurs embedded in wealth building value chains. Each case differs as a reflection of local assets, and the value chains provide examples of working to support entrepreneurship at different levels of development.

In Oregon, a partnership of organizations implemented a substantial pilot of the WealthWorks program in 2014. Six regions were selected through a competitive process and received four months of an intensive technical assistance program. Seven businesses were awarded a total of $95,000 of direct business investment. Regions received ongoing technical assistance at different rates. This business investment model, started by the Ford Foundation and continued on a smaller scale in Oregon, is unique among rural development programs which often stop at technical assistance (Yellow Wood Associates, 2015).

This program translated RWC principles into a set of guidelines for selecting businesses for targeted resources. Qualitative interviews of seven recipient businesses at two time periods following the assistance document how this program has built rural wealth through a value chain approach in a variety of contexts. We organize our seven businesses into three different types of value chains: established, early stage, and connecting multiple sectors. Within this structure we describe different types of rural entrepreneurial businesses, how the businesses have evolved, and how investing in each business has generated wealth throughout the value chain. Although limited in scope, these seven business investment grants provide tangible evidence of the rural wealth creation framework’s impact in a regional economy.

This paper advances the successful implementation of RWC practice by documenting how targeted business investments within a value chain built multiple forms of wealth. We provide exploratory evidence of how thoughtful consideration of business characteristics and placement within a value chain can increase the potential that the targeted businesses are able to generate immediate streams of rural wealth. We organize our findings by a business’s relative position in a value chain and note that our examples are not exhaustive. Our results illustrate a range of entrepreneurial actions and degrees of innovation that can be assisted through RWC work and provide examples of how to implement the RWC concepts to target business assistance.

References: Johnson, T.G., Raines, N., & Pender, J.L. (2014). Comprehensive wealth accounting. In J.L. Pender, T.G. Johnson, B. Weber, & J.M. Fannin (Eds.), Rural wealth creation (pp. 30–54). New York, NY: Routledge.

Lyons, T. S., & Wyckoff, B. (2014). Facilitating community wealth building: Understanding the roles played and capacities needed by coordinating institutions. Community Development, 45(5), 443-457.

Pigg, K., Gasteyer, S., Martin, K., Keating, K., & Apaliyah, G.P. (2013). The community capitals framework: An empirical examination of internal relationships. Community Development, 44, 492–502. doi:10.1080/15575330.2013.814698

Pender, J., Alexander Marre, and Richard Reeder. (2012a). Rural Wealth Creation: Concepts, Measures, and Strategies. American Journal of Agricultural Economics. 94(2): 535-541.

Pender, John, Alexander Marré, and Richard Reeder. (2012b) Rural Wealth Creation: Concepts, Strategies and Measures. ERR-131, U.S. Department of Agriculture, Economic Research Service. March.

Pender, J. L., Weber, B. A., Johnson, T. G., & Fannin, J. M. (Eds.). (2014). Rural wealth creation. Routledge.

Ratner, S., & Markley, D. (2014). Linking rural assets to market demand: Wealth creation value chains in rural America. Local Economy, 29(4-5), 345-353.

Schmit, T. M., Jablonski, B. B., Minner, J., Kay, D., & Christensen, L. (2017). Rural wealth creation of intellectual capital from urban local food system initiatives: Developing indicators to assess change. Community Development, 48(5), 639-656.

Yellow Wood Associates. 2015. Formulating a Sustainable Economic Development Process for Rural America: Final Report to the Ford Foundation on WealthWorks. Available: https://yellowwood.org/assets/resource_library/resource_docs/formulating-a-sustainable-economic-development-process-for-rural-america.pdf

ABSTRACT. In order to meet the social and economic challenges of the modern era, rural economies are evolving. Globalization and sheer necessity have forced many communities to end an over-reliance on agriculture and enhance agribusiness systems. From Africa to the North America, efforts are underway to transform rural economies by expanding infrastructure, improving living standards, and diversifying production.

In the South Western and Central regions of Uganda, agriculture is the main sector of employment for households. The Uganda Bureau of Statistics estimates that about 72 percent of all Uganda’s working population is employed in agriculture. Much of Uganda’s rural transformation was built on agricultural income growth that benefited poor households. According to the World Bank, poverty reduction among households in agriculture accounts for 79 percent of national poverty reduction from 2006 to 2013.

The Black Belt is a region of the Southern United States where rural communities have historically faced acute poverty because of the area’s relative isolation and lack of economic development. According to the 2000 U.S. Census, the 11 states that make up the Southern Black Belt have a combined rural poverty rate of 18.7 percent, translating into almost 1 in every 5 rural residents living in poverty. Population decline in rural areas, inadequate education programs, low educational attainment, poor health care, urban decay, substandard housing, and high levels of crime and unemployment have become hallmarks of this chronically underfunded and marginalized region.

This study is the first of two-phase mixed research examining the impact of agriculture and non-agricultural activities on rural development in parts of Uganda and the United States. Through statistical and document analyses, this study seeks to ascertain the methods, programs, and investments necessary to promote economic independence and global interdependence among rural communities. A two-phase triangulation design is used to set appropriate quantitative and qualitative parameters and examine specific phenomena to determine if findings from disparate data sets converge upon a single understanding of the investigated research problem. During the first phase, all data collected will be analyzed using quantitative methods. Results from data analysis conducted during the first phase will be examine to interpreted and determine a convergence or divergence of certain ideas.

By employing a panel data model consisting of portions of select states that make up the Black Belt region in the United States observed over a fifteen-year period from 2000 through 2015; and examining statistical data from the South Western region of Uganda, this study seeks to determine the economic impacts of agribusiness and public or private investments on rural economies. Preliminary results from assessments of these different data points suggest best practices from the two countries can have a significant impact on rural communities in both regions.

ABSTRACT. The primary product extracted by households from forests in developing countries is fuelwood. According to the National Sample Survey data on India, the dependence of households in rural areas on fuelwood for cooking was 73.4% in 2001-02 and 75.4% in 2006-07. Use of kerosene or dung cakes had gone down in the same period. The poor are on average much more dependent on fuelwood for their energy requirements than richer households (Jodha, 1986). The natural resource base therefore plays an important role in the wellbeing of the poor in such countries by providing resources such as fuelwood (Dasgupta, 2010). In this paper, I propose to estimate the impacts of the National Rural Employment Guarantee Scheme (NREGS), an anti-poverty workfare program in India, on household choice of fuel and its usage. Workfare programs are among the most widely implemented programs in developing countries aimed at reducing poverty, increase resilience especially in times of agricultural lean seasons, and improve rural infrastructure. “Self-selection” by participants in these programs reduce the information problems governments face in targeting the right households that require financial assistance (Besley and Coate, 1992; Sukhtankar, 2016). The NREGS is the largest workfare program in the world. It aims to reduce poverty by providing yearly public works employment to the poorest rural households at minimum wages. NREGS affects forest resources through direct and indirect effects. Direct effects occur through implementation of public works undertaken as part of NREGS like conservation programs and rural infrastructure building. Indirect effects are realized through changes in household consumption patterns of forest dependent products like fuelwood or construction wood due to changes in income and time use because of program participation. I use three rounds of nationally representative National Sample Survey (NSS) data to estimate the impacts of NREGS on household fuel consumption. Our treatment districts are those where NREGS was implemented in phase 1 while the control districts are those in which NREGS was implemented in phase 2. I use a difference-in-differences approach to estimate the impact of NREGS on type of fuel used in rural areas exploiting the fact that NREGS was phased in over time into three cohorts of districts. In my previous study, I found that the impact of NREGS on forest vegetation, as measured by NDVI, is significant and negative. Moreover, these effects were stronger in districts that were more forested during pre-treatment baseline levels. The effects of NREGS on fuel usage is expected to be more on the poorest households since they are more likely to work under NREGS. Therefore, I will also estimate heterogenous treatment effects by quartiles of forest cover by district and by quartiles of household consumption expenditure. Most studies have explored the efficacy of workfare programs in improving social indicators. However, few have looked at the impacts of these or cash transfer programs on natural resources and the environment (eg. Alix-Garcia et.al, 2013). Moreover, given the current debates on the sustainability of fuel switching by households in developing countries (Hanna et al., 2016), our study will contribute to the understanding of the impacts of anti-poverty workfare programs on forest resource utilization.   Works cited:

Alix-Garcia, Jennifer, Craig McIntosh, Katharine R. E. Sims, and Jarrod R. Welch, The Ecological Footprint of Poverty Alleviation: Evidence from Mexico's Oportunidades Program, Review of Economics and Statistics, May 2013, Vol. 95, No. 2, Pages 417-435

Barbier, E. B. (2010). Poverty, development, and environment. Environment and Development Economics, 15(6), 635-660.

Besley, Timothy and Stephen Coate, Workfare versus Welfare: Incentive Arguments for Work Requirements in Poverty-Alleviation Programs, The American Economic Review, 1992, 82 (1), 249-261.

Bhargava, Anil K., The Impact of India's Rural Employment Guarantee on Demand for Agricultural Technology (November 1, 2014). IFPRI Discussion Paper 01381

Bhattacharya, H., & Innes, R. (2012). Income and the environment in rural India: Is there a poverty trap?. American Journal of Agricultural Economics, 95(1), 42-69.

Dasgupta, P. (2010). The place of nature in economic development. In Handbook of development economics (Vol. 5, pp. 4977-5046). Elsevier.

Foster, A., and M. Rosenzweig. 2003. "Economic Growth and the Rise of Forests." Quarterly Journal of Economics 118:601-37.

Hanna, R., Duflo, E., & Greenstone, M. (2016). Up in smoke: the influence of household behavior on the long-run impact of improved cooking stoves. American Economic Journal: Economic Policy, 8(1), 80-114.

Jodha, N. S. (1986). Common property resources and rural poor in dry regions of India. Economic and political weekly, 1169-1181.

Sukhtankar, Sandip, India's National Rural Employment Guarantee Scheme: What Do We Really Know about the World's Largest Workfare Program? India Policy Forum, 29 November, 2016

ABSTRACT. One of the major challenges for local government is management of solid waste, which has become a major line item in local budgets. The ASCE Infrastructure report card grades the U.S. overall a C+ on solid waste management; on average U.S. communities recycle about 35% of municipal solid waste, with the majority still going to landfills. However, recent shifts in the recycling industry have caused major disruptions in recycling markets. In particular, new polices by China, which was a major consumer of items like paper and paperboard, have removed this market or made it much more expensive. In addition, trade policies which have resulted in tariffs on metals and other goods have shifted the markets for these products as well.

This paper presents an overview of the recent changes in the recycling industry, and subsequent changes in markets and derived demand. We then focus on one particular commodity which has proved to be especially problematic, mixed paper. Mixed paper (“junk mail”, glossy paper, paperboard, etc.) accounts for over 30% of the U.S. waste stream. This paper presents ongoing research on the current state of the recycled mixed paper industry as well as an investigation into possible outlets for mixed paper. As of January 2018, China has imposed quality standards which have effectively eliminated much of the market for U.S. paper and paperboard. As a result, transfer stations run by local governments, which used to be paid for mixed paper, now must pay to dispose of it. Because of this, a new solution must be implemented to avoid this major cost.

Three possible outlets have been identified: large animal bedding, fuel pellets, and compost. Available information was gathered on past use of recycled mixed paper in these contexts. Research has included input from universities that have tested mixed paper animal bedding as well as companies currently using the material to make animal bedding and fuel pellets. It was determined the average cost of different types of animal bedding and standard wood pellets is around $200 per ton, which is being used to estimate possible profits of the mixed paper’s final product. It has been confirmed that recycled mixed paper is compostable, both after use as animal bedding and before.

Using this information, potential production procedures have been created and costs have been estimated for machinery, labor, storage, and transportation. Pilot programs will test mixed paper as both animal bedding and fuel pellets. Several local farms will test the animal bedding, and one school will be chosen to test the fuel pellets. The pilot program will allow for the perfection of the production process before making the final product available for purchase to the general public. This study will present preliminary information on potential costs and revenues of alternative uses and markets for this major segment of our waste stream.

ABSTRACT. In this paper, we estimate the economic impacts of environmentally friendly vehi-cles on the national and regional economy in Japan. Recently, the hybrid and elec-tric vehicles gradually become popular. The industrial structure will be affected by the production of new generation vehicles. A new technology in the automobile industry has an influence on not only own industry but also other industries. The regions where the automobile firms are concentrated will be affected by a new technology. In this study, we explore the economic impacts of shifting the produc-tion system in the automobile industry from the conventional automobile technol-ogy to an electric and hybrid vehicle technology using the national and multire-gional input-output models in Japan.

ABSTRACT. Since 2011, UDC have installed many sustainability projects in its campus and introduced new sustainability related majors to its students. This research examines the University of the District of Columbia (UDC) student’s knowledge on the campus sustainability projects and evaluates three intervention techniques to enhance the student’s knowledge and awareness. Eight non-environmental-science majored, undergraduate classes (105 students in total) participated in this research. The students divided into two groups: intervention and non-intervention groups. The non- intervention classes (29 students) considered as our baseline. The intervention group is further divided into three sub-groups and was invited to be involved in a level of sustainability educational intervention. The interventions include: sustainability signage (23 students), sustainability lecture (32 students), and in-person tour (21 students) of the UDC sustainability projects. Each intervention lasted for 20 minutes and the students in each intervention were exposed to the UDC sustainability projects, which was followed by a survey. Findings show that just 28% of our baseline group knew about the UDC sustainability projects. The interventions significantly increased the student’s knowledge on the UDC sustainability projects. In lecture intervention group, 58% of the students indicated good knowledge of the projects after going through a 20 minutes presentation. The Tour and Signage Intervention groups also indicated 48% and 27% awareness respectively after going through a 20 minutes intervention. Regression results show moving from signage intervention to tour and lecture intervention, on average, increases students’ awareness by 0.76 sustainability knowledge score (highly significant). Interestingly, regression analysis also shows that the older and Hispanic students are more aware of sustainability challenges compare to younger and non-Hispanic students. As the result of this research, since 2018 we installed 5 interactive signage (digital signs) of campus sustainability project to attract student’s to the sustainability projects and facilitate students’ learning through these projects. We also use Google Analytics to capture students’ interactions with the interactive signage and understand how students use the signage across the campus. The collected data shows 20% improvement in students’ knowledge on campus sustainability projects.

ABSTRACT. It has long been understood that strategic tax interactions exist between neighboring municipalities. Far less is known about how those same municipalities interact in terms of expenditure. Existing research has shown that municipalities will react positively to the spending of their neighbors. These spending interactions are underestimated in two different ways. Using a Tiebout framework it is demonstrated that suburbs and rural areas surrounding principal cities treat spending by the principal city differently then that of other suburbs, and visa versa. Lumping all neighbor spending together understates the amount of interaction taking place. They are also underestimated due to the focus on total expenditure. Subcategories of expenditure can have contradicting signs in interaction.

ABSTRACT. There is long-standing debate about how the presence of foreign-born population affects home values and induces native flight. Using 1990 and 2016 census data, this article contributes to this existing literature by examining the impact of foreign-born population on median home value and white flight in Louisville, the largest city in Kentucky. In particular, we explore the spillover effect of foreign-born population beyond neighborhood boundaries and utilize geographic weighted regression (GWR) to tackle spatial heterogeneity complicating the immigrant/neighborhood relationship. Our findings show negative but predominantly insignificant associations between foreign-born population and median home value, while strongly supporting a racial white flight hypothesis. We also show that these relationships vary across space: foreign-born population is a salient predictor in home value depreciation in poorer inner-city neighborhoods whereas white flight is most notable in affluent suburban neighborhoods.

ABSTRACT. The Tinbergen Principle states that if we pursue n independent policy goals, then we need at least n independent policy instruments to reach them all. This paper first explains the principle (Tinbergen, 1952) and then explores its implications for policy-making. This contribution is aimed at students and practitioners of economic policy who are not yet familiar with the Tinbergen Principle.

ABSTRACT. A rich set of data derived from the Bureau of Economic Analysis’ Survey of New Foreign Direct Investment in the United States offers insights into the question of how firms select locations for greenfield investment. Using data from the surveys for recent years, I analyze determinants of the choice of location for new investments by metropolitan statistical area (MSA). The bulk of new foreign investment is drawn to MSAs that correspond to the largest global cities in the United States. I separately identify how the investments to these MSAs are attracted by aspects of global cities including a diverse population, advanced producer services, and the presence of international transportation links. Even after controlling for these aspects, I find that investments in an MSA are positively correlated with global city status, suggesting that there are other attractive aspects of global cities that I have not yet identified.

ABSTRACT. Regression discontinuity (RD) design, while useful, is potentially weak to cross-sectional interactions common in both spatial and network models. Using local-linear methods often leaves the weight matrix non-invertible, while higher order polynomials suffer from problems of poor inference. Omitting these cross-sectional interactions has been shown to introduce bias and/or inefficiency into the parameter estimates. Using a combination of residualization and numerical integration we develop a method -- using the Spatial Durbin framework -- which retains the full weight matrix and allows for a full accounting of these cross-sectional interactions. We demonstrate this generalized local-linear model using U.S. House of Representatives election results from 1946-1996. Close election wins have indirect effects which previously were unaccounted and contribute approximately 5% to neighboring district vote shares on average.

ABSTRACT. The Bureau of Economic Analysis (BEA) publishes annual personal consumption expenditures (PCE) statistics for the 50 states and the District of Columbia. PCE statistics are particularly important as they account, on average, for about two-thirds of domestic final consumption, and are thus a key driver of economic growth. BEA is now exploring the feasibility to expand these statistics to include metropolitan areas and potentially counties, to provide a richer picture of the geographic variation in consumer spending. More importantly, PCE statistics at a local level can assist in the assessment of households’ welfare, inform policymaking, and illustrate differences in consumer preferences across local areas. In this paper, we describe preliminary source data and an exploratory methodology to produce experimental metropolitan area and county PCE statistics from 2012 forward. In addition, this paper describes other ongoing research related to regional PCE statistics, including research into the feasibility of producing real-dollar estimates of PCE by state and quarterly PCE by state statistics.

ABSTRACT. The lack of subnational trade data has dampened the development of reliable regional and multiregional models for regional policy development. So, most researchers and vendors of regional and interregional economic models continue to rely on location quotients, supply-demand pool techniques, or minor modifications of them, despite knowing that they under-estimate interregional trade. In turn, this leads to upward bias in intra-regional multiplier effects as modeled via Leontief processes. Unfortunately, “bigger is better” is the mantra of policy makers when it comes to the measurement of multiplier effects. So, our inability to properly measure trade at the subnational level is rarely deemed an issue of concern. Our goal in this piece is to analyze the relative viability of estimates of intraregional trade—so called “regional purchase coefficients” (RPCs). We do so for manufacturing sectors in 28 EU countries using the World I-O Database. The RPC-estimating techniques we use are akin to those of a supply/demand ratio, Treyz & Stevens (1985), Többen & Kronenberg’s (2015) and a negative binomial estimator of our own devise. We also approximate RPCs of non-goods-producing industries using estimated supply/demand ratios and assume output in all 28 countries have EU average value-added shares. We then test and compare them by regionalizing an aggregate EU input-output (IO) table to see how closely the 28 country IO tables are approximated by each approach in turn. We also evaluate their ability to replicate the country Leontief inverses and output multipliers.

ABSTRACT. IMPLAN used the gravity model to estimate inter-regional trade flows among different regions in U.S. Even though the gravity model has been considered the best option to model human commuting patterns, it requires more data to estimate the parameters. For many international regions, there are no data available to estimate any parameters; therefore, we explored a parameter-free method to model the inter-regional trade flows. This new methodology applied the generalized radiation model and the multiregional generalized RAS (MRGRAS) techniques, which could estimate inter-regional trade flows consistent with a system of regional supply and use tables. This paper describes in detail the method applied in the regionalization process, which includes two steps. The first step is to calculate the initial estimation of the inter-regional trade flows by applying the generalized radiation model proposed by Masucci et al. (2013). And the second step is to balance the inter-regional trade flows by applying the MRGRAS technique proposed by Temursho et al. (2018). The trade flows are estimated by distributing the trade over the regions, given the amount produced and consumed in each region. The radiation model was first proposed by Simini et al. in 2012. It became prevalent on the grounds of its simple form and parameter-free property; however, even though it gives competitive results, the “universality” assumption has limited the applicability since certain elements with substantial importance like spatial scale and heterogeneity are overlooked in the model. In 2013, Masucci et al. have introduced a generalized radiation model, which overcame the limits while maintaining its nature of universality, and the results were competitive with the results from the gravity model. The radiation model was introduced to track human movements in mobility systems. In our project, we apply the model to track goods and services movements, which are the commodity trade flows among the regions. The MRGRAS technique is an extension of the GRAS method. Besides the substitution effects and fabrication effects in the original GRAS technique, this extension added a third dimension of “technology effects”, which indicates the general rise or fall in importance of product i for sector j. In our project, instead of adding the “technology effects”, we add the “regional effects” as the third dimension, which could capture the trade flows between region i and region j, and also control the aggregated trade flows to the total regional supply and use. The new parameter-free method could provide a simply way for us to estimate the inter-regional trade flows for any regions consistent with a system of regional supply and use tables.

ABSTRACT. Local officials and economic development groups frequently request “retail gap” analyses to help guide their business and community development efforts. This research explores alternative methods for evaluating a community’s retail portfolio relative to its peers. This research will identify strengths and weakness of commonly-used approaches and data sources. The goal of the research is to assist local decision-makers in making more informed decisions when soliciting and using this type of analysis.

ABSTRACT. Current climate policies that aim to reduce greenhouse gas emissions (GHG) mostly regulate production-based emissions which are based on where emissions are generated. However, unlike other environmental emissions with only local impacts, GHG emissions have global impacts on climate change. Regulating production-based emissions may lead to carbon leakage which means the emission reductions of carbon-constrained regions could be partially offset by the increased emissions of unconstrained regions. Carbon leakage also exists within the U.S. since some states have their own climate policies, such as California’s cap-and-trade program. Trade is one major source of leakage as it geographically separates the consumption of goods and services from the environmental burdens of production. Goods and services can be imported from unconstrained regions rather than being produced in constrained regions. However, research on embodied emissions in U.S. domestic trade is very limited due to data constraints. This paper uses the Multi-Region Input-Output (MRIO) framework to estimate CO2 emissions (the major component of GHG) embodied in the U.S. interstate trade. By estimating CO2 emissions embodied in bilateral trade among U.S. states, my research will provide a comprehensive picture of “who pollutes for who,” which can contribute to examining the extent of carbon leakage so that the net impacts of state climate and economic policies would be clear. MRIO framework can provide economy-wide analysis including the entire production chain and account for the heterogeneity of production patterns among states. It allows me to track emissions to final consumption through the production chain no matter where the emission is produced so that helps me answer “who pollutes for who.” The results suggest that some state (such as New York) should be responsible for higher emissions as the emissions embodied in the imports from other states exceed those embodied in the exports; the contrast case may be true for some states in the Midwest. My finding can be used to advise the policy-making process in examining the impacts of sub-national climate policies on surrounding regions.

ABSTRACT. As the women's educational attainment level and labor participation level increased, dual-earner households also increased. However, there are conflicting analysis results about the commuting behaviors of the dual-earner household. In this research, I tried to analyze the dual-earner household's commuting behaviors and verify if the household responsibility hypothesis still explains the dual-earner household's commuting behaviors. For the analysis, I used the Census Bureau's 2017 American Community Survey Public Use Microdata Sample (PUMS) 1-year dataset and conducted a series of ordinary least squares regression models. The dual-earner households were divided into different types of households by educational attainment level and income level of the spouses; (1) Husband>Wife (2) Husband=Wife (3) Husband Wife), but not the Household Type 3 (Husband

ABSTRACT. Self-employment is potentially more risky and may offer less security than paid-employment. At the same time, employment in some industries is more risky overall. For married couples, there may be a joint decision to minimize employment risk. However, there is also evidence that “risk loving” people are attracted to each other, thus they may have a higher tolerance for risk. Using micro-level data from the Panel Study of Income Dynamics (PSID), we examine the self-employment decision for married women and whether or not having a spouse working in an unstable, or risky, industry, affects this decision. We also examine whether this varies by region.

ABSTRACT. Expansions of Medicaid family planning services have been associated with decreases in pregnancy rates. Access to a broader range of medical, non-family planning services may influence pregnancy rates as well if the increased exposure to medical services spills over to other behavior. We consider this possibility by using individual level data in a difference-in-difference estimation during the ACA expansion of Medicaid. Previous state provision of family-planning services allows us to isolate the additional effect of increased access to non-family planning medical services. We find that access to a broader range of medical services reduces the probability of pregnancy by 27%.

ABSTRACT. In this note we show a closer link between second-degree stochastic dominance (SD) and measures of inequality and poverty than previously recognized. For a normalized second-degree SD curve, the weighted area between the curve and that of the equal distribution characterizes the class of decomposable transfer-sensitive inequality measures. For a censored second-degree SD curve, the weighted area between the curve and that of the zero-poverty distribution characterizes the class of decomposable distribution-sensitive poverty measures. Some extensions are considered and the properties of the weighting functions are also explored.

ABSTRACT. This research address the determinants of the recruitment of children at a Municipality level. To explore this Hypothesis I estimate a spatial probit model. Our probit model analyzes the effects of the peace talks and agreements with paramiltary armies and guerrilla army FARC. The interpretation of the coefficients follows the methodology set up by Lacombe and Lesage(2018).

ABSTRACT. The presence of universities and colleges in a region plays an important role in supporting regional economic development and stability. Especially, they acted as a buffer to absorb labor forces during the Great Recession, with an increase in total enrollment in colleges in the U.S. In response to the Great Recession, the overall federal funding for higher education increased but the state funding declined. Moreover, there are substantial differences in the change of federal and state funding across states, which would have different implications for students entering the labor market when they graduate. Previous studies suggest that contracting state funding may shift the financial burden to students, which would be an important consideration for students choosing jobs. This research aims to examine the effect of federal and state funding on students’ labor market performance and its spatial variation. We explore the data in the College Scorecard of the U.S. Department of Education that incorporates data related to higher education from different sources and covers a wide range of topics, including institutional characteristics, the price and costs, and the graduates’ earnings. However, it does not include the financial data of institutions from the Integrated Postsecondary Education Data System (IPEDS), which has information on federal and state funding. Merging the two data sets involves dealing with the parent-child problem because most institutions only report the aggregated financial data at the parent-institution level, for example, the main campus of the Pennsylvania State University, not at the branch level. Since one of the purposes of this research is to check the state variation of the effect of federal and state funding, we collapse the branch-level data into the parent institutions. In the regression analysis, we set up a multilevel random-slope model to regress the changes in graduates’ earning on the changes in federal and state funding at the institution level, and the slope is modeled at the state level to add the state labor market conditions and state fixed effects into the model. What we are also interested in and will explore using the rich information in the dataset is to see the impact of federal and state funding on other outcome measures, such as, research activities, graduation and retention rates.

ABSTRACT. The wealth of extant research has focused on understanding drivers of economic and social costs of disasters (for an extensive review of literature please see Kousky 2014) and how effective public disaster programs are in mitigating these aftereffects (Davlasheridze et al. 2018; Davlasheridze & Miao, 2018). However, relatively little is known about human health implications of disasters realized not only in terms of lives lost and physical injuries, but also in the form of other more subtle, long-term health problems such as declining mental health, subsequent substance dependence and possible drug-related fatalities. Recent research has shown drug-overdose fatalities to increase in response to presidentially declared disasters in the United States, and this after controlling for major socioeconomic and demographic determinants of substance related mortality (Goetz and Davlasheridze 2018). There are multiple channels through which disasters can exacerbate the substance dependence. Disaster experience (i.e., financial loss, loss of immediate family member), physical injuries and subsequent decline in emotional wellbeing (Osofsky et al. 2009; Calvo et al. 2014; Goetz et al. 2015) that may manifest in the long-term are just a few obvious links that may lead to emergence or continuation of drug dependency (Sulivan et al. 2006). Furthermore, disasters may also affect access to and the affordability and quality of healthcare services (Babar and Rinker 2006).

Understanding how disasters contribute to the opioid crisis not only during and in the immediate aftermath, but also how they manifest in the long term is important and will inform not only the immediate response strategy and disaster contingency plans (i.e., short-term strategy) but will also help to efficiently allocate and manage resources to address emergent health problems in the long-term.

Catastrophic disaster incidents have increased worldwide in recent decades, and the United States particularly has seen a significant surge in the frequency of high consequence weather and climatic disasters. The year 2017 alone was associated with 16 separate large-scale weather events, causing over $300 billion in cumulative losses affecting more than 4.7 million people directly (NOAA 2018). Given the preponderant scientific consensus that climate change will alter the frequency and severity of extreme weather events (e.g., floods, hurricanes, surge events), it is of paramount importance to understand potential health implications of such shocks and how well health care services are prepared in handling challenges disasters generate at multiple fronts for human health. In this paper, we focus on understanding how experience with extreme flooding events may linger over time and contribute to drug-related mortality in the United States. Floods represent one of the most prevalent environmental hazards responsible for the most lives lost and the largest economic losses, and are concern in almost all parts of the US (Perry, 2000). We use data on all US counties and show a significant rise in drug overdose mortality in response to extreme flooding events. More importantly, our results also suggest that impacts of floods linger over the long-term, with a significant rise in death rates seen even 10 years after the catastrophic disaster incident. The opioid crisis has been recognized as a national health emergency and, in some area, the state’s governors (e.g., Pennsylvania) have even initiated health emergency declarations similar to federal disaster declarations as a way to mobilize resources to address the opioid epidemics. Understanding how the two (substance dependence and disasters) are interconnected will further inform both local and national challenges and opportunities for improvements when dealing with natural and health crisis.

ABSTRACT. As in many countries, losses to natural disasters in the United States have been staggering. To date, researchers have focused primarily on quantifying the cost of natural disasters and future vulnerability in terms of changes in private sector output, physical damage and loss of life. Only recently have researchers begun to also examine the fiscal costs of disasters to governments, which are affected differently than the private sector. The vast majority of this research, however, has focused at the national level at the exclusion of the effects on local governments. This paper begins to fill that void by examining how natural disasters affect the finances of governments at the county level. The focus on the local level is important both to help local policymakers build resilience to future disasters and to help better understand what to expect if a disaster has already struck an area.

Disasters affect local governments differently than national governments. On one hand, local governments are often fortunate to be able to benefit from transfers from higher levels of government. However, they are vulnerable in terms of their dependence on funding coming through, coming through in a timely fashion, and their dependence on much smaller tax bases.

To examine how losses from natural hazards affects local government finances, this paper examines the effects of natural disasters on county-level government general revenues, revenue sources and expenditures in the years following the disasters. The paper further examines whether the number of above-average disasters (based upon damage totals) experienced within the previous five years decreases revenues and expenditures in counties. The paper utilizes moderated random-effects regression models based on data from the Census of Governments to explore the effects of natural disasters.

In terms of expenditures, the paper finds that general direct expenditures remained steady post-disaster with the exceptions of the cases of metropolitan county hazard loss or in the event of above-average disasters. In terms of revenues, the paper finds non-linear fiscal impacts due to disasters. As damage from natural hazards increases, revenue from own sources for metropolitan counties declines, as do intergovernmental revenues for non-metropolitan counties in the following two years. However, in the case of the above-average damage disasters, counties experienced significant increases in intergovernmental revenue post-disaster. This is an indication that local governments may be particularly susceptible to and need to prepare better for moderate-sized natural disasters.

ABSTRACT. Little is known about how natural disasters affect public housing, especially regarding the role of governmental disaster aid in assisting the recovery of those relying on government-subsidized affordable housing. In this paper we empirically examine the impact of natural disasters on the provision of public housing in the United States. Based on a national sample of counties over the period 2005-2016, we find that floods cause a significant negative shock to the provision and affordability of public housing in the aftermath of their occurrence: the amount of public housing units declines, average waiting time becomes longer, the tenant-paid rents and occupancy rates both increase significantly. We also find that the FEMA’s Public Assistance (PA) program grants have a positive effect in restoring the supply of public housing, as well as in lowering the rents tenants pay for public housing and the occupancy rates. The PA grant also reduce the need for the existing governmental expenditures on subsiding public housing.

ABSTRACT. International Data Occupational Suite Data Region-Specific Foreign Trade Rates 2012 BEA Benchmark and 5-Year Censuses

ABSTRACT. The United States has been experiencing an unprecedented level of low unemployment following 8 years of consecutive growth. While this is a positive indicator for the economy, it is critical to note that another measure has been rising during this time and that is the job vacancy rate. While in the short-run this might be considered a positive situation, such a market inefficiency over a prolonged period of time could be detrimental to the economy. Using a regional setting this paper explores State level matching efficiencies across space and time. The data is then combined with a unique business cycle dating and turning point algorithm to better understand how regional macro forces change the efficiency of the labor market. The preliminary findings from this paper show that regional business cycles have varying effects on a State’s matching efficiency. This speaks to the heterogeneity of regional labor markets that often get lost in aggregate studies. In addition, the work sheds new light on how the health of regional economies could be improved by better understanding regional matching processes.

ABSTRACT. Bogota, Colombia´s capital city displays a dramatic heterogeneity in its inside, manifested in social and economic differences among the population. While the majority of the localities in the northwest are related with a higher socioeconomic status, the south is completely the opposite.

On the one hand, the northwest presents favourable indices connected with infrastructure, security, location of industries more related with technology, presence of large firms and elevated wellbeing in the households in the area. On the other hand, the south is linked to low-income families, working class households; deficient and damaged public and private infrastructure, small and medium firms, informality, insecurity, etc.

As the growth into the city has reached their physical boarders, growth and industrial spillovers have come up, meaning an increasing search made by firms and families for moving outside, to the south and the north - northwest to nearby municipalities. Enquiringly, the socioeconomic conditions reflected in those municipalities seem to replicate the ones inside of the city as similar wellbeing or scarcities have been observed.

Labour market is one of the proxies that we can consider, to measure the different social conditions of the population and to determine whether if there is any spatial dependence between the municipalities with the proximities to the different zones, northwest and south, in Bogota. To this case it is going to be considered the municipalities of the provinces of Soacha and Sabana Occidente in Cundinamarca.

The objectives of this research are two: 1. To find out if there is any dependence between the social conditions in Bogota and how they are reflected in the municipalities and 2. To develop a set of indices of decent work and how those have evolve between 2014 and 2017, from the perspective of the following strategies: Generation of work and employment, Promotion of the guarantee of fundamental labour rights, Promotion of social dialogue, Extension of protection and social security and territorialization of politics.

As methodology, it is made a characterization of actors of the labour market in the municipalities using different qualitative methods, then the results are going to be contrasted with a quantitative exercise using data from the Multipurpose Survey from 2014 and 2017 to configurate the results in 10 dimensions for the working population. Finally, it is going to be displayed an econometric spatial model to measure the spatial dependence between zones in Bogota and the municipalities.

ABSTRACT. While certainly not a new position, vocal public opinion in the United States encourages immigrants to adopt English as their new standard of communication. Evidence for English-First (EF) movements is clearly visible on social and mainstream media. Even within immigrant communities, the support for heritage language use is an embattled topic. In this analysis, we ask whether there is a benefit to continuing the use of a heritage language in a predominantly monolingual economy. This paper adds a unique spatial dimension to the already vibrant literature on the returns to language by looking at the proportion of a region’s population that natively (i.e. in the home) speaks a non-English language. Using the Public Use Microdata Sets, we a find evidence of a concave relationship between the proportion of a state’s population speaking a heritage language and various economic outcomes, controlling for other factors. The results suggest a “sweet spot” population proportion in which benefits to speaking a heritage language are maximized. For a given region, our results have clear policy implications as states seek to target new in-migrant populations, as well as a more nuanced understanding of the relationship between minority-languages and their utility for their speakers. Of particular social importance are the insights these data provide in the backdrop of EF movements.

ABSTRACT. Many cities aspire to have vibrant entrepreneurial ecosystems that are relevant to the digital economy—can they? To answer the question, this paper examines the economic history of Vancouver British Columbia and examine the recent entrepreneurial activities in the city along with the data that measures the vibrancy of the entrepreneurial ecosystem and growth. In recent years, the startup in its entrepreneurial ecosystem has generate more activity than ever and a new entrepreneurial mindset is manifesting itself. The only hindrance is the access to the lack of capital to promote entrepreneurship. But the entrepreneurs are undeterred, and the rise of entrepreneurship still has been increasing. While there is no indication that the various data points converge, the proposed analysis may lead us to three insights. First, legacy industry is disconnected from the new tech hub in an entrepreneurship ecosystem when the economy has shifted from the ‘Main street’ mode to a ‘digital’ mode. Second, while there are recent success stories in Vancouver British Columbia, entrepreneurship activities remain moderate to somewhat strong despite a bottom-up effort to bolster the entrepreneurial spirit in Vancouver. Finally, cluster advantages and positive network externalities may be occurring in Vancouver British Columbia.

ABSTRACT. In 2017, 4.2 million Asian women accounted for 6.3 percent of the U.S. civilian female population aged 16 and older, according to data from the Current Population Survey (CPS). Despite often being classified as a uniform group, these Asian women display considerable variation in their American labor force experience. Anecdotally women born in the different countries of Asia, the largest nation of origin is China, are “known” to have different labor outcomes. I hope to dispel the notion that there is uniformity of the Asian female experience in American labor markets and to articulate some explicit differences in the market’s responses to their human capital characteristics as well as any cultural discrimination and self-selection bias where it might exist. I use the 2017 American Community Survey (ACS) to explore these differences and to identify the driving factors of the diversity between Chinese women and women from other Asian communities insofar as they affect labor force participation within the U.S across the four U.S. Census Regions.

ABSTRACT. The quality of life literature highlighted the importance of natural and consumption amenities in households’ preferences for cities to spur economic growth. As policymakers look to invest scarce resources in specific local amenities, they may be missing an important perspective, what women want. As women’s labor force participation and wages have increased and as women wait longer to get married, their relative control over household resources and household decision-making has likely increased. Furthermore, the literature on household bargaining provides evidence of gender differences in preferences over spending even within households. However, the quality of life literature does not seem to make any such distinction along gender lines. Thus, we separately estimate for unmarried men and women the quality of life across cities in the U.S. Our results suggest that city valuations by men and women are correlated, suggesting some commonality in preferences for location-based amenities, but there are also significant deviations in the valuations of some cities. We find men and women do have common preferences for some amenities such as natural amenities, but that there are meaningful differences in preferences across gender lines especially for some public goods.

ABSTRACT. American women now outnumber men among bachelor’s and graduate degree holders, and this is especially true in rural communities. In this paper, I examine how gender disparities in higher educational attainment vary across age cohorts in rural vs. urban US counties and use regression analysis to explore connections between gender (im)balance in college-educated adult populations and local economic conditions. I also employ local indicators of spatial association (LISA) to determine whether counties with disproportionately female college-educated populations are spatially autocorrelated. These findings will shed light on a little-studied phenomenon with potential implications for gender equality and local economies.

ABSTRACT. Entrepreneurship and self-employment are key drivers of economic development and employment growth across every US State. However, there remains less evidence as to the labor market conditions that are conducive to entrepreneurial activity and even less on how gender is intertwined geographically. Conditions of the labor market have an overarching effect on self-employment through both wage rates as well as available alternative sources of employment but is this gender specific? In this paper, we attempt to fill these gaps in the literature by exploring labor market conditions and self-employment across US States. Unique to this study is the inclusion of HWOL vacancy postings for each State. This data provides a snapshot of the labor market conditions associated with new employment prospects, thus giving a more robust estimate of the true alternative to self- employment. The study also includes wage levels as a way of determining the effect they have on the level of self-employment. A key contribution of the paper is the ability to estimate the opportunity cost of self-employment by gender. Preliminary results show evidence that high numbers of vacancies are associated with entrepreneurial decisions; we find a positive relationship between new vacancies and self-employment in general.

ABSTRACT. Competition for factors of production, including competition for residents, affects the public services provided in the communities. In this paper, we focus on local transport systems. Many specialists question the effectiveness of the current U.S. top-to-bottom transportation institutional arrangement in which the federal government plays a dominant role and recommend a shift toward a decentralized organization of the transport system. We examine how such a shift would affect the observed levels of transport investment. We consider a model of two cities, and assume, as in Brueckner and Selod (2006), that transport systems are characterized by different time and money costs. We compare the transport systems decided by a central authority (a state or federal government) to those chosen by local jurisdictions in a decentralized way. In the latter case, local transportation authorities choose the system that maximizes residents' welfare, competing for residents or workers. Our analysis shows that a shift toward a decentralized arrangement of the transportation system would generally lead to overinvestment (relative to the centralized case), and the extent of this bias depends on the specific factors that drive transport authorities in deciding the transportation system, on the landownership structure, and on the financing arrangements in place. In a more general setup, the paper also shows that when cities differ in their productivity levels, the more productive city will tend to overinvest in transportation systems that connect the two cities, and the less productive city will tend to underinvest in those systems.

ABSTRACT. The impact of mobility on work commute time is examined for the Pittsburgh, PA metropolitan statistical area (MSA) from 2010 through 2016. Results show that movement within the same county and movement from a different county are both associated with shorter commutes for census tracts in the full MSA sample. Movement within the same county is not associated with reduced commuting time in Allegheny County although it is associated with reduced commuting time in the surrounding counties. Examining movement from a different county, census tracts in Allegheny County experience reduced commuting time if they have received a greater share of migrants from outside the county Differences based on race are also examined and show that census tracts with more black residents endure longer commutes and migration does not reduce commuting time.

ABSTRACT. The monocentric city model in the tradition of Alonso, Muth and Mills is the theoretical workhorse of urban economics. However, there is little empirical evidence in support of the model. Assuming a Cobb-Douglas functional form, in this paper, we use 2000’s Zillow housing data for Cleveland, OH, as well as income and fuel prices to fit an econometric model and find very reasonable coefficient estimates in support of the monocentric city model.

ABSTRACT. **Undergraduate Poster Abstract**

This study analyzes the effects of subjective and objective job insecurity among workers in the United States, and whether persistent job insecurity has an especially large impact on mental wellbeing. Previous researchers have found a link between job insecurity and mental wellbeing in Canada and Europe. This study aims to increase the amount of literature on this research question, while also including new variables such as whether or not an individual feels they could find a job if they lost their job today. This survey question has not been included in previous studies. Analysis includes panel data from the Americans' Changing Lives Study, 1986-1989, to measure objective and subjective job insecurity, perceived mental health (based on the Kessler-6 Psychological Distress Index, K6) as well as other controlled factors. Results show that having been unemployed within the past three years, as well as feeling relatively job insecure, have statistically and economically significant impacts on the K6 measure of psychological distress at the 1% level, even when controlling for factors such as cigarette and alcohol use, gender, race, income, and age in both 1986 and 1989.

ABSTRACT. **Undergraduate Poster Abstract**

Every parent has a dream for their children to be more successful than themselves. This objective was studied by Chetty et al (2014). They identified youth in rural counties having a higher income rank than their parents as compared to their counterparts in urban counties. However, they were unable to determine if the success of the youth in rural areas was strictly influenced by migration. My research extends this work by asking the question if migration of youth outside their adolescent geographic home as adults is associated with greater upward mobility compared those that stayed in their home towns as adults. I use data from Chetty et al (2018). He provides income rank for youth overall and that stay in their home commuting zones. I impute algebraically the income rank of those that out-migrate. I calculate descriptive statistics of upward mobility on both cohorts. I test for equivalence of means on multiple geographic cohorts. Finally, I replicate some of the regression analysis in Weber et al (2018) to identify any significant differences in the associative factors affiliated with upward mobility between the two cohorts. References: Chetty et al (2018). The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility. https://opportunityinsights.org/wp-content/uploads/2018/10/atlas_paper.pdf Chetty et al (2014). “Where is the Land of Opportunity?” The Geography of Intergenerational Mobility in the United States. Quarterly Journal of Economics. 129(4): 1553-1623. Weber et al (2018). Intergenerational Mobility of Metropolitan and Nonmetropolitan Youth in the United States: A Spatial Analysis. Regional Science Policy and Practice. 10:87-101.

ABSTRACT. **Undergraduate Poster Abstract**

In this project, I am investigating the relationship between pay and performance in professional soccer in the English Premier League using panel data from the 2011/12 season to the 2017/18 season. I find a quadratic relationship between pay and performance controlling for performance from the past two seasons, showing that increased salary increases performance up to a certain point, and then increased salary decreases performance past this point. The results also show that player performance is affected by the size of the salary increase that players receive, as well as the number of years they have remaining on their contract.

ABSTRACT. **Undergraduate Poster Abstract**

This study examines the effects of pharmaceutical expenditures on life expectancy for a sample of OECD member countries. Through constructing an aggregate life expectancy production function encompassing economic, demographic and lifestyle input variables, it was found that pharmaceutical consumption has a positive and statistically significant impact on the life expectancy for both genders at ages 40, 60, 65 and 80. Additionally, the impact of pharmaceutical consumption on longevity increases as age increases, and there were greater effects on the life expectancy of males than females. For example, a one-percentage point increase of total pharmaceutical expenditures as a share of total health expenditures, would lead to a lagged 0.3% increase in the life expectancy of a female at age 40 and a 0.4% increase in the life expectancy of a male at age 40. This translates to a 46-day and a 56-day increase when applied to the sample mean, respectively.

ABSTRACT. **Undergraduate Poster Abstract**

This study examines the impacts of policies and investments on the transition to the use of more renewable energy in the first part of the 21st century. Using state-level data, we consider the impact on the transition to renewable energy due to financing, policies, and the energy technologies each state can accommodate. We also control for other factors such as population, income, and employment using data from the U.S. Census and Bureau of Economic Analysis. Yearly energy production data are taken from the U.S. Energy Information Administration and policy and project investment data from the U.S. Department of Agriculture. Our analysis provides insight into the factors the lead to the expansion of renewable energy in yearly output by state, and overall in the United States.

ABSTRACT. **Undergraduate Poster Abstract**

The evaluation of the success of unconventional monetary policy can be done in multiple ways, one being by examining money supply changes. This study looks to examine how changes in M2 money supply, along with other economic and financial indicators can be used to predict economic recovery during times of recession. Linear probability models are used to determine the effectiveness of these indicators in recognizing changes in economic conditions to indicate economic recovery. The model finds multiple indicators, including changes in real M2 money supply, to be significant in indicating recovering economic conditions during recessionary periods in the US economy.

ABSTRACT. Since 2013, the US Office of Management and Budget has recognized the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas. Under the 2010 standards, statistical areas are determined using the five-year Census American Community Survey data. These data are used to generate point estimates of commuting between counties in the US with a Margin of Error (MOE). The goal of this study is to determine the extent to which the MOE effects the definition of counties’ distinction as an outlier metropolitan or non-core county and to study the implications of total population by CBSA category for the US and major regions.

In order to observe the effects, I created a data set using information provided by the Census Bureau and the American Community Survey to model the delineations in Microsoft PowerBI. The margin of error was used to compute both high and low extremes for commuting and new definitions for counties were observed based on counties moving above or below the 25% employed threshold of working in a central metropolitan county. These definitions were compared using interactive maps and graphs along with related population tables to provide detailed descriptive statistics. These results have implications for major federal government programs that distribute funds based on CBSA status such as federal departments of Housing and Urban Development, Transportation and Agriculture.

Reference: US Census Bureau Commuting (Journey to Work) (2019). https://www.census.gov/topics/employment/commuting/guidance/flows.html

ABSTRACT. **Undergraduate Poster Abstract**

Using the data obtained through the Integrated Public Use Microdata Series from the Current Population Survey (1995 – 2015), I investigate the effect marriage and parenthood have on the gender wage gap in Utah and compare it to the United States as a whole. The gender wage gap is growing at a quicker rate in Utah than the national average. There is an equal percentage change in income with age in both genders and race does not show to be significant in Utah, which may be due to the lack of racial diversity. Education level has a stronger impact on women’s wages than it does for men. Utah parents see an above average expansive effect on the gender wage gap with the addition of more children. Culture may attribute to larger family sizes and could be a key indicator of gender wage inequality in Utah.

ABSTRACT. **Undergraduate Poster Abstract**

This research aims to measure the effect from implementation of policies towards safer neighborhoods. The past local two governments of Santiago de Cali, Colombia, have created a policy to improving the public lighting through quantity and qualitiy around near public parks. The policy expands public lighting in some locations and modernize the light source from sodium vapor technology to white light. We aim to analyze the impact of lighting features (including intensity, location, amount and others) over crime dynamics in Santiago de Cali city. We use data from police registers and Using data available from Security observatory and Light Data (Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB)). We will examine changes in crime variables with respect to the incidence of the light public policy for the period of 2014 to 2017. We implement the model repeat sales measures. Through the preliminary results show some improvements on safety and crime dropping after the policy.

ABSTRACT. **Undergraduate Poster Abstract**

In this study, I investigate the relationship between state-level policies and teenage fertility levels from 1990-2016, focusing specifically on Medicaid eligibility expansions through income- and duration-based waivers. I offer four main conclusions: First, income waivers lead to lower teen birth rates as expected and can account for approximately 5% of the decline in the teen birth rate. Second, Title V Abstinence Funding can account for 10% of the decrease in the teen birth rate. Third, the Minor Parent Provision (MPP) and State Children's Health Insurance Program (S-CHIP) appear to be associated with increased teen birth rates, but I suspect that this is because states with inherently higher teen birth rates have implemented MPP and S-CHIP in an effort to curb teen fertility. Last, it appears that regions, which were used to capture cultural differences across the United States, are significantly correlated with changes in the teen birth rate; states in the northeast and midwest tend to have lower teen birth rates than states in the south.

ABSTRACT. **Undergraduate Poster Abstract**

Following the model of the Gini coefficient and Stigler's (1958) survival principle, this paper develops a useful measure of farm size that combines two conventional statistics (reported sales and acreage). Our measure reflects the entire distribution of farm sizes rather than relying on point measurements such as the mean or median value, which have remained constant since 1975 according to the United States Department of Agriculture. As a result, we can model the historic evolution of farm size in U.S. field-crop production since 1959 without relying on potentially arbitrary definitions or truncating available data. This paper initially offers a simple graphic illustrating dynamic changes in the market; it is essentially a story of competition between small and large farms. Based on the graphic, we use basic calculus to derive the Share-weighted Size Index which is our proposed measure for farm size. We consider the Share-weighted Size Index superior to conventional measures of farm size such as the mean or median. Relying on the Share-weighted Size Index to measure farm size, we document substantial variation in the timing and magnitude of increasing farm sizes across time, across field-crop, and across U.S. regions. We then use regression analysis to estimate the Share-weighted Size Index and find that farm size generally decreases in opportunity costs, a result at odds with Kislev and Peterson (1982).

ABSTRACT. **Undergraduate Poster Abstract**

Violence against women is a concern that resonates continually in social circles, in the media and public intervention. Colombia is among the countries with the highest prevalence rates of domestic violence in the world. This research aims to analyze the determinants of domestic violence in Colombia, applying probabilistic models - Probit. We use data from the National Demographic and Health Survey (DHS), which includes the characteristics of women, their partners, and their environment. In addition we try to consider other variable the limits of the social relationship imposed by her partner, the sexual education received, the existence of domestic violence among the parents of the victims, and other explanatory variables. Preliminary results show, in Colombia, the probability of suffering physical, sexual and psychological violence, is correlated to their conditions and their familiar background to violence.

ABSTRACT. **Undergraduate Poster Abstract**

Driving across rural America, it becomes very obvious that populations are shifting and opportunities for upcoming graduates who want to serve rural America may need to think carefully about where they focus their job searches. Among many drivers of change is a change in who is farming. Changes in farm size composition of the Southern United States will impact industries surrounding farming in years to come. The fluctuation in operation sizes can be caused by productivity changes, natural disasters, policy, cost of living, profitability and many other things.

We downloaded data from the USDA NASS regarding the number of farm operators for various farm size classes across the Southeast from the 2002 and 2012 Census of Agriculture. Each map shows percent change in farm operators for a size class. For example, in operation sizes of one acre to nine acres the percentage change in Texas is largely negative while we find that the majority of Tennessee has a high positive percentage in this size operation. Overall what was conclude is that each state throughout the south no matter the operation size was not static and each county of every state was apt to change whether that be for a positive or negative change in each size subset. When searching for opportunities post-graduation, it may be useful for students to focus on areas where small acreages experienced increases if one intends to focus on landscaping or in areas where large farms increased if one intends to focus on production inputs.

ABSTRACT. **Undergraduate Poster Abstract**

In light of the recent and ongoing global refugee crisis, this paper’s research question addresses the impacts of refugee resettlement on the host economy and, specifically, the effects that refugee resettlement has at the city level. Due to numerous international conflicts, the number of refugees and displaced persons has reached approximately 68.5 million worldwide, with only 102,800 being resettled as of June 2018 according to the UNHCR. To combat the negative outcomes of this international situation, governments must adapt to the increasing demand for refugee resettlement. The results of this paper provide a frame of reference from which policymakers can inform constituents about the economic impact of refugee resettlement. For this analysis, I construct a 13-year panel data set for 20 mid-size cities in the Western US. Using a linear regression with city and year fixed effects, the relationship between the annual refugee resettlement rate within a city and its impact on median household income is analyzed, while taking into account influential demographic factors. The effects of refugee resettlement are further broken down based on the economic status of the host city. Refugee resettlement is found to have a significant positive impact on median household income in the long term for low income host cities.