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Articles 1 - 30 of 342
Full-Text Articles in Social and Behavioral Sciences
Tax Streams, Land Rents, And Urban Land Allocation, Yugang Tang, Zhihao Su, Yilin Hou, Zhendong Yin
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 …
The Mundlak Spatial Estimator, Badi H. Baltagi
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
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
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
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 …
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
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 …
The Two-Way Mundlak Estimator, Badi H. Baltagi
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
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
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
“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
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
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
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 …
Lasso For Stochastic Frontier Models With Many Efficient Firms, William C. Horrace, Hyunseok Jung, Yoonseok Lee
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
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
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
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
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
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 …
Behavioral Bias In Occupational Fatality Risk: Theory, Evidence, And Implications, Perry Singleton
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
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 …
Robust Dynamic Panel Data Models Using ��-Contamination, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix
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 …
Trimmed Mean Group Estimation, Yoonseok Lee, Donggyu Sul
Trimmed Mean Group Estimation, Yoonseok Lee, Donggyu Sul
Center for Policy Research
This paper develops robust panel estimation in the form of trimmed mean group estimation for potentially heterogenous panel regression models. It trims outlying individuals of which the sample variances of regressors are either extremely small or large. The limiting distribution of the trimmed estimator can be obtained in a similar way to the standard mean group estimator, provided the random coefficients are conditionally homoskedastic. We consider two trimming methods. The first one is based on the order statistic of the sample variance of each regressor. The second one is based on the Mahalanobis depth of the sample variances of regressors. …
The Effect Of Industrial Robots On Workplace Safety, Ling Li, Perry Singleton
The Effect Of Industrial Robots On Workplace Safety, Ling Li, Perry Singleton
Center for Policy Research
This study measures the effect of industrial robots on workplace safety at the commuting zone level, exploiting potentially exogenous variation in robot exposure due to technological progress. Workplace safety is measured by workers involved in severe or fatal accidents inspected by the Occupational Safety and Health Administration. From 2000 to 2007, we find that one additional robot in exposure per 1,000 workers decreased the OSHA accident rate at the mean by 15.1 percent. We also find that robot exposure decreased OSHA violations and accidents more likely to be affected by robot penetration, specifically those involving machinery or electrical.
Depth-Weighted Forecast Combination: Application To Covid-19 Cases, Yoonseok Lee, Donggyu Sul
Depth-Weighted Forecast Combination: Application To Covid-19 Cases, Yoonseok Lee, Donggyu Sul
Center for Policy Research
We develop a novel forecast combination based on the order statistics of individual predictability when many forecasts are available. To this end, we define the notion of forecast depth, which measures the size of forecast errors during the training period and provides a ranking among different forecast models. The forecast combination is in the form of a depth-weighted trimmed mean, where the group of models with the worst forecasting performance during the training period is dropped. We derive the limiting distribution of the depth-weighted forecast combination, based on which we can readily construct forecast confidence intervals. Using this novel forecast …
Dynamic And Non-Neutral Productivity Effects Of Foreign Ownership: A Nonparametric Approach, Yoonseok Lee, Mary Lovely, Hoang Pham
Dynamic And Non-Neutral Productivity Effects Of Foreign Ownership: A Nonparametric Approach, Yoonseok Lee, Mary Lovely, Hoang Pham
Center for Policy Research
This paper studies two novel productivity characteristics of foreign acquisition on high-tech manufacturing firms: the dynamic and the non-Hicks-neutral effects. A dynamic productivity effect of foreign ownership arises when adoption of foreign technology and management practices takes time to fully realize. Furthermore, these dynamic adjustments may be capital or labor augmenting as adoption of advanced production technologies tends to have non-neutral productivity implications in developed countries. We propose and implement an econometric framework to estimate both effects using firm-level data from China's manufacturing sector. Our framework extends the nonparametric productivity framework developed by Gandhi, Navarro and Rivers (2020), in which …
Technical Efficiency Of Public Middle Schools In New York City, William C. Horrace, Michah W. Rothbart, Yi Yang
Technical Efficiency Of Public Middle Schools In New York City, William C. Horrace, Michah W. Rothbart, Yi Yang
Center for Policy Research
Using panel data and a “true” fixed effect stochastic frontier model, we estimate persistent and transient technical inefficiency in mathematics (Math) and English Language Arts (ELA) test score gains in NYC public middle schools from 2014 to 2016. We compare several measures of transient technical inefficiency and show that around 58% of NYC middle schools are efficient in Math gains, while 16% are efficient in ELA gains. Multivariate inference techniques are used to determine subsets of efficient schools, providing actionable decision rules to help policymakers target resources and incentives.
The Effects Of Vietnam-Era Military Service On The Long-Term Health Of Veterans: A Bounds Analysis, Xintong Wang, Carloa A. Flores, Alfonso Flores-Lagunes
The Effects Of Vietnam-Era Military Service On The Long-Term Health Of Veterans: A Bounds Analysis, Xintong Wang, Carloa A. Flores, Alfonso Flores-Lagunes
Center for Policy Research
We analyze the short- and long-term effects of the U.S. Vietnam-era military service on veterans’ health outcomes using a restricted version of the National Health Interview Survey 1974-2013 and employing the draft lotteries as an instrumental variable (IV). We start by assessing whether the draft lotteries, which have been used as an IV in prior literature, satisfy the exclusion restriction by placing bounds on its net or direct effect on the health outcomes of draft avoiders. Since we do not find evidence against the validity of the IV, we assume its validity in conducting inference on the health effects of …
Health Have, Health Have Nots In A Time Of Covid-19, Sandro Galea
Health Have, Health Have Nots In A Time Of Covid-19, Sandro Galea
Center for Policy Research
In this brief, my goal is to talk about something which has animated a lot of my thinking and writing in the past decade. It is how our health is fundamentally socially patterned and reflects the world around us. This has been true for decades in this country, and one could also argue, globally, however this brief will focus on this topic at the national level. As you will see, I will talk mostly of health haves and health have nots in general, but as we progress, show how COVID-19 has made this evermore apparent.
A Panel Data Model With Generalized Higher-Order Network Effects, Badi Baltagi, Sophia Ding, Peter Egger
A Panel Data Model With Generalized Higher-Order Network Effects, Badi Baltagi, Sophia Ding, Peter Egger
Center for Policy Research
Many data situations require the consideration of network effects among the cross-sectional units of observation. In this paper, we present a generalized panel model which accounts for two features: (i) three types of network effects on the right-hand side of the model, namely through weighted dependent variable, weighted exogenous variables, as well as weighted error components, and (ii) higher-order network effects due to ex-ante unknown network-decay functions or the presence of multiplex (or multi-layer) networks among all of those. We outline the model, the basic assumptions, and present simulation results.