Social and Behavioral Sciences Commons^™

Tax Streams, Land Rents, And Urban Land Allocation, Yugang Tang, Zhihao Su, Yilin Hou, Zhendong Yin

Center for Policy Research

This paper examines the fiscal motives behind municipal governments' decisions to allocate commercial and residential land when two categories of land use are subject to different fiscal revenue alternatives: business-related tax and/or land rent. We use urban parcel-level land transfers during China’s peak period of urbanization, match commercial parcels with residential parcels, and find significant price discounts on commercial parcels relative to adjacent residential parcels. The observed discounts arise from the future tax flows from commercial use, i.e., expected taxes from developed commercial land reduce its transfer price. We conduct a structural estimation to examine the implications on land use …

Behavioral Science Interventions Could Increase Snap Comprehension And Awareness Among Military Families, Colleen Heflin, Hannah Patnaik, Leonard M. Lopoo, Siobhan O'Keefe

Population Health Research Brief Series

Food insecurity is more common among military families than the general population, and the transition from active service to civilian life is a time of heightened risk. The Supplemental Nutritional Assistance Program (SNAP) is designed to support food security among low-income families. Many eligible military and veteran families do not enroll in SNAP due to a lack of information, stigma, and administrative barriers. This brief highlights findings from a survey experiment conducted in 2022 and 2023 to assess how small changes to SNAP informational flyers, such as simplifying information provided about SNAP, highlighting that other veterans use SNAP, and emphasizing …

The Mundlak Spatial Estimator, Badi H. Baltagi

Center for Policy Research

The spatial Mundlak model first considered by Debarsy (2012) is an alternative to fixed effects and random effects estimation for spatial panel data models. Mundlak modelled the correlated random individual effects as a linear combination of the averaged regressors over time plus a random time-invariant error. This paper shows that if spatial correlation is present whether spatial lag or spatial error or both, the standard Mundlak result in panel data does not hold and random effects does not reduce to its fixed effects counterpart. However, using maximum likelihood one can still estimate these spatial Mundlak models and test the correlated …

Treatment For Mental Health And Substance Use: Spillovers To Police Safety, Monica Deza

Center for Policy Research

We study the effect of community access to mental health and substance use treatment on police officer safety, which we proxy with on-duty assaults on officers. Police officers often serve as first-responders to people experiencing mental health and substance use crises, which can place police officers at risk. Combining agency-level data on police officer on-duty assaults and county-level data on the number of treatment centers that offer mental health and substance use care, we estimate two-way fixed-effects regressions and find that an additional four centers per county (the average annual increase observed in our data) leads to a 1.3% reduction …

Covid-19 Has Strengthened The Relationship Between Alcohol Consumption And Domestic Violence, Monica Deza, Aaron Chalfin, Shooshan Danagoulian

Center for Policy Research

A large body of evidence documents a link between alcohol consumption and violence involving intimate partners and close family members. Recent scholarship suggests that since the onset of the COVID-19 pandemic and subsequent stay-at-home orders, there has been a marked increase in domestic violence. This research considers an important mechanism behind the increase in domestic violence during the COVID-19 pandemic: an increase in the riskiness of alcohol consumption. We combine 911 call data with newly available high-resolution microdata on visits to bars and liquor stores in Detroit, MI and find that the strength of the relationship between visits to alcohol …

Unemployment, Alcohol, And Tobacco Use: Separating State Dependence From Unobserved Heterogeneity, Monica Deza

Center for Policy Research

Previous literature presents mixed evidence on the effect of alcohol consumption on labor market outcomes. On one hand, heavy alcohol consumption has been shown to have detrimental effects on labor market outcomes. On the other hand, moderate consumption is positively associated with wages and employment. Despite substantial reduced form evidence, previous literature has not been able to separately identify the causal pathways linking moderate versus heavy alcohol use to labor market performance due to the lack of natural experiments that only target moderate versus heavy drinking, as well as limitations of available structural methods that model state dependence and unobserved …

Aca Medicaid Expansions Did Not Significantly Improve Maternal Morbidity, Pinka Chatterji, Hanna Glenn, Sara Markowitz, Jennifer Karas Montez

Population Health Research Brief Series

Rising rates of severe maternal morbidity in the U.S. highlight the unmet need for continuous and comprehensive health care for women before, during, and after pregnancy. This data slice summarizes findings from a study that tested whether ACA Medicaid expansions helped reduce severe maternal morbidity, including transfusion, ruptured uterus, unplanned hysterectomy, eclampsia, and the need for intensive care. Results show little evidence that the ACA expansions improved maternal morbidity, other than reducing the need for blood transfusions.

Moving Policies Toward Racial And Ethnic Equality: The Case Of The Supplemental Nutrition Assistance Program, Alfonso Flores-Lagunes, Hugo B. Jales, Judith Liu, Norbert L. Wilson

Center for Policy Research

We analyze the role played by the Supplemental Nutrition Assistance Program (SNAP) in alleviating or exacerbating inequality across racial and ethnic groups in food expenditures and in the resources needed to meet basic food needs (the “food resource gap”). To do this, we propose a simple framework that decomposes differences across groups in SNAP benefit transfer levels into three components: eligibility, participation, and generosity. This decomposition is then linked to differences in food expenditures and the food resource gap. Our results reveal that among the three components, differences in eligibility contribute the most to SNAP benefits differentials for Black and …

New York Camp Econometrics Xvii Program, Center For Policy Research

Camp Econometrics-Programs

No abstract provided.

The Two-Way Mundlak Estimator, Badi H. Baltagi

Center for Policy Research

Mundlak (1978) shows that the fixed effects estimator is equivalent to the random effects estimator in the one-way error component model once the random individual effects are modeled as a linear function of all the averaged regressors over time. In the spirit of Mundlak, this paper shows that this result also holds for the two-way error component model once this individual and time effects are modeled as linear functions of all the averaged regressors across time and across individuals. Woolridge (2021) also shows that the two-way fixed effects estimator can be obtained as a pooled OLS with the regressors augmented …

Racial Disparities In School Poverty And Spending: Examining Allocations Within And Across Districts, Robert Bifulco, Sarah Souders

Center for Policy Research

Using recently available school-level finance data, we compare exposure to low-income classmates and average per pupil spending for black, Hispanic, and white students. Using within metropolitan area comparisons, we find that the typical black and Hispanic students attend schools with much higher proportions of low-income students than the typical white student, and that per pupil spending in the typical black and Hispanic students’ schools is higher than in the typical white student’s school. Drawing on estimates of the additional spending required to provide low-income students equal educational opportunity, we find that it is unlikely that the additional spending in schools …

The Fiscal Sustainability Of Retiree Health Care Benefits Among New York State School Districts, Robert Bifulco, Minch Lewis, Iuliia Shybalkina

Center for Policy Research

We examine spending on retiree health care as a percentage of revenues for a sample of New York State school districts. The fiscal burden of these benefits grew from 2010 to 2021, and big city school districts have faced the largest burdens. Assuming CBO forecasts regarding growth in health care costs and continuation of recent trends in revenue growth, we project that the burden of retiree health care benefits will exceed 10 percent of revenue by 2050. Projected burdens are greatest big city and high need rural districts. We discuss cutting benefits and pre-funding as possible policy responses.

“Model Minorities” In The Classroom? Positive Evaluation Bias Towards Asian Students And Its Consequences, Ying Shi, Maria Zhu

Center for Policy Research

The fast-growing demographic group of Asian Americans is often perceived as a “model minority.” This paper establishes empirical evidence of this stereotype in the context of education and then analyzes its consequences. We show that teachers rate Asian students’ academic skills more favorably than observationally similar White students in the same class, even after accounting for test performance and behavior. This contrasts with teachers’ lower likelihood of favoring Black and Hispanic students. Notably, teachers respond to the presence of any Asian student in the classroom by exacerbating Black-White and Hispanic-White assessment gaps. This suggests that the “model minority” stereotype can …

Robust Dynamic Space-Time Panel Data Models Using Ε- Contamination: An Application To Crop Yields And Climate Change, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix

Center for Policy Research

This paper extends the Baltagi et al. (2018, 2021) static and dynamic ε-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach de-parts from the standard Bayesian framework in two ways. First, we consider the ε-contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and the ε-contamination priors use Zellner (1986)’s g-priors for the variance-covariance matrices. We propose a general “toolbox” for a wide range of specifications which includes the …

Cities In A Pandemic: Evidence From China, Badi H. Baltagi, Ying Deng, Jing Li, Zhenlin Yang

Center for Policy Research

This paper studies the impact of urban density, city government efficiency, and medical resources on COVID-19 infection and death outcomes in China. We adopt a simultaneous spatial dynamic panel data model to account for (i) the simultaneity of infection and death outcomes, (ii) the spatial pattern of the transmission, (iii) the inter-temporal dynamics of the disease, and (iv) the unobserved city- and time-specific effects. We find that, while population density increases the level of infections, government efficiency significantly mitigates the negative impact of urban density. We also find that the availability of medical resources improves public health outcomes conditional on …

The Conditional Mode In Parametric Frontier Models, William C. Horrace, Hyunseok Jung, Yi Yang

Center for Policy Research

We survey formulations of the conditional mode estimator for technical inefficiency in parametric stochastic frontier models with normal errors and introduce new formulations for models with Laplace errors. We prove the conditional mode estimator converges pointwise to the true inefficiency value as the noise variance goes to zero. We also prove that the conditional mode estimator in the normal-exponential model achieves near-minimax optimality. Our minimax theorem implies that the worst-case risk occurs when many firms are nearly efficient, and the conditional mode estimator minimizes estimation risk in this case by estimating these small inefficiency firms as efficient. Unlike the conditional …

New York Camp Econometrics Xvi Program, Center For Policy Research

Camp Econometrics-Programs

No abstract provided.

Lasso For Stochastic Frontier Models With Many Efficient Firms, William C. Horrace, Hyunseok Jung, Yoonseok Lee

Center for Policy Research

We apply the adaptive LASSO (Zou, 2006) to select a set of maximally efficient firms in the panel fixed-effect stochastic frontier model. The adaptively weighted L1 penalty with sign restrictions for firm-level inefficiencies allows simultaneous estimation of the maximal efficiency and firm-level inefficiency parameters, which results in a faster rate of convergence of the corresponding estimators than the least-squares dummy variable approach. We show that the estimator possesses the oracle property and selection consistency still holds with our proposed tuning parameter selection criterion. We also propose an efficient optimization algorithm based on coordinate descent. We apply the method to estimate …

Spatial Wage Curves For Formal And Informal Workers In Turkey, Badi H. Baltagi, Yusuf Soner Başkaya

Center for Policy Research

This paper estimates spatial wage curves for formal and informal workers in Turkey using individual level data from the Turkish Household Labor Force Survey (THLFS) provided by TURKSTAT for the period 2008-2014. Unlike previous studies on wage curves for formal and informal workers, we extend the analysis to allow for spatial effects. We also consider household characteristics that would affect the selection into formal employment, informal employment, and non-employment. We find that the spatial wage curve relation holds both for formal and informal workers in Turkey for a variety of specifications. In general, the wages of informal workers are more …

Bayesian Estimation Of Multivariate Panel Probits With Higher-Order Network Interdependence And An Application To Firms' Global Market Participation In Guangdong, Badi H. Baltagi, Peter H. Egger, Michaela Kesina

Center for Policy Research

This paper proposes a Bayesian estimation framework for panel-data sets with binary dependent variables where a large number of cross-sectional units is observed over a short period of time, and cross-sectional units are interdependent in more than a single network domain. The latter provides for a substantial degree of flexibility towards modelling the decay function in network neighborliness (e.g., by disentangling the importance of rings of neighbors) or towards allowing for several channels of interdependence whose relative importance is unknown ex ante. Besides the flexible parameterization of cross-sectional dependence, the approach allows for simultaneity of the equations. These features should …

The Link Between Gentrification, Children’S Egocentric Food Environment, And Obesity, Christopher Rick, Jeehee Han, Spencer Shanholtz, Amy Ellen Schwartz

Center for Policy Research

While advocates argue that gentrification changes the neighborhood food environment critical to children’s diet and health, we have little evidence documenting such changes or the consequences for their health outcomes. Using rich longitudinal, individual-level data on nearly 115,000 New York City children, including egocentric measures of their food environment and BMI, we examine the link between neighborhood demographic change (“gentrification”), children’s access to restaurants and supermarkets, and their weight outcomes. We find that children in rapidly gentrifying neighborhoods see increased access to fast food and wait-service restaurants and reduced access to corner stores and supermarkets compared to those in non-gentrifying …

Using Pupil Transportation Data To Explore Educational Inequities And Outcomes: A Case Study From New York City, Sarah Cordes, Samantha Trajkovski, Christopher Rick, Meryle Weinstein, Amy Ellen Schwartz

Center for Policy Research

This article explores how researchers can use pupil transportation data to explore key questions about the role of transportation in educational access and equity, such as how students get to school and the effect of transportation on student outcomes. We first describe different sources of transportation data that are available to researchers, provide a brief review of relevant literature, and discuss potential sources of measurement error in pupil transportation data. Next, we use administrative data from New York City to illustrate how pupil transportation data can be used to understand transportation eligibility and assignment as well as to describe the …

Towering Intellects? Sizing Up The Relationship Between Height And Academic Success, Stephanie Coffey, Amy Ellen Schwartz

Center for Policy Research

Do tall students do better in school? While a robust literature documents higher earnings among taller people, we know little about the potential academic origins of the height earnings gradient. In this paper, we use unique student-level longitudinal data from New York City (NYC) to examine the link between height and academic outcomes, shedding light on underlying mechanisms. The centerpiece of our empirical work is a regression linking academic outcomes to height, measured as a z-score normalized to same grade/sex peers within schools. We estimate a meaningful height gradient for both boys and girls in ELA and math achievement in …

Is Offense Worth More Than Defense In The National Basketball Association?, Justin Ehrlich, Joel Potter

Sport Management - All Scholarship

Motivated by the popular sports saying, “Offense sells tickets, defense wins championships,” we use Forbes revenue data to quantify whether offense really does sell more ‘tickets’ than defense in the National Basketball Association (NBA). Employing team offensive and defensive win shares as measures of offensive and defensive proficiency, we find offensively oriented teams generate the same amount of revenue as do defensively oriented teams, other things equal. Our results suggest that both profit-maximizing and win-maximizing teams should value offensively and defensively players equivalently (per unit). Thus, in an efficient free agent market, we would expect equilibrium player salaries for offensive …

Behavioral Bias In Occupational Fatality Risk: Theory, Evidence, And Implications, Perry Singleton

Center for Policy Research

Behavioral bias in occupational fatality risk is introduced to the theoretical framework of hedonic wages, yielding an endogenous risk ceiling that increases social welfare. Empirically, bias is most evident among workers with no high school diploma, who do not report relatively greater exposure to death in high fatality rate occupations. These findings suggest that extant population estimates of value of statistical life are biased downwards and should be factored by at least 1.35. Under reasonable assumptions, simulations suggest an optimal risk ceiling between 73.0 to 85.9 percentile of the population distribution of occupational fatality risk.

What Makes A Classmate A Peer? Examining Which Peers Matter In Nyc Elementary Schools, William C. Horrace, Hyunseok Jung, Jonathan L. Pressler, Amy Ellen Schwartz

Center for Policy Research

Generalizing the group interaction model of Lee (2007), we identify and estimate the effects of student level social spillovers on standardized test performance in New York City (NYC) elementary schools. We leverage student demographic data to construct within-classroom social networks based on shared student characteristics, such as a gender or ethnicity. Rather than aggregate shared characteristics into a single network matrix, we specify additively separate network matrices for each shared characteristic and estimate city-wide peer effects for each one. Conditional on being in the same classroom, we find that the most important student peer effects are shared ethnicity, gender, and …

Do Minimum Charity Care Provision Requirements Increase Provision Of Charity Care In Nonprofit Hospitals?, Michah W. Rothbart, Nara Yoon

Population Health Research Brief Series

Nonprofit hospitals receive significant federal, state, and local tax exemptions, partly based on the rationale that nonprofit hospitals provide public goods and services. Through Minimum Charity Care Provision (MCCP) requirements, nonprofit hospitals are required to spend a certain percentage of their revenues on charity care. However, it is not clear whether these requirements increase spending on charity care. This brief summarizes findings from research examining the differences in provisions of charity care across different hospital market sectors – non-profit, for-profit, and government. Findings suggest that MCCP requirements for nonprofit hospitals do not lead to more charity care. If anything, targeting …

The U.S. Child Care Subsidy Program Is Underused But Well-Positioned To Promote Racial Equity, Taryn Morrissey, Colleen Heflin, William Fannin

Population Health Research Brief Series

Child care is expensive and difficult to find, especially for infants and toddlers. Compared to their higher-income peers, children from lower-income families are less likely to attend out-of-home early childhood care – which tend to be more expensive but provides more stability and is higher quality than home-based care. This contributes to disparities in school readiness and later life outcomes. This brief summarizes findings from a recently published paper examining administrative data from the Commonwealth of Virginia. Findings suggest that children are least likely to receive subsides when they are infants and toddlers despite early childhood care being the most …

Robust Dynamic Panel Data Models Using ��-Contamination, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix

Center for Policy Research

This paper extends the work of Baltagi et al. (2018) to the popular dynamic panel data model. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the standard Bayesian framework in two ways. First, we consider the ε-contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and the ε-contamination priors use Zellner (1986)'s g-priors for the variance-covariance matrices. We propose a general "toolbox" for a wide range of specifications which includes the dynamic …

Economics For Everyday Life: Opportunity Cost And Marginal Benefit, Christian Palencia

English Language Institute

Economics is a social science that may feel unreal or even useless for many people. Its concepts and definitions can be abstracts, complex and unpragmatic. However, the comprehend of some ideas of this science can be the key for a success decision making process for normal people’s life.

Contrary to popular belief, the economy is not about money, it is focused on studying the problem of shortage. Resources such as time and money are scarce, consequently, understanding the basic of economics is fundamental for everyone not only for economists. The opportunity cost and marginal benefit are an examples of two …