Showing results 1 to 8 of approximately 8.(refine search)
In-migration and Dilution of Community Social Capital
Consistent with predictions from the literature, we find that higher levels of in-migration dilute multiple dimensions of a community's level of social capital. The analysis employs a 2SLS methodology to account for potential endogeneity of migration.
AUTHORS: Hotchkiss, Julie L.; Rupasingha, Anil
Individual Social Capital and Migration
This paper determines how individual, relative to community, social capital affects individual migration decisions. We make use of nonpublic data from the Social Capital Community Benchmark Survey to predict multidimensional social capital for observations in the Current Population Survey. We find evidence that individuals are much less likely to have moved to a community with average social capital levels lower than their own and that higher levels of community social capital act as positive pull-factor amenities. The importance of that amenity differs across urban/rural locations. We also confirm that higher individual social capital is a negative predictor of migration.
AUTHORS: Hotchkiss, Julie L.; Rupasingha, Anil
Facts and Fiction in Oil Market Modeling
Baumeister and Hamilton (2019a) assert that every critique of their work on oil markets by Kilian and Zhou (2019a) is without merit. In addition, they make the case that key aspects of the economic and econometric analysis in the widely used oil market model of Kilian and Murphy (2014) and its precursors are incorrect. Their critiques are also directed at other researchers who have worked in this area and, more generally, extend to research using structural VAR models outside of energy economics. The purpose of this paper is to help the reader understand what the real issues are in this debate. The focus is not only on correcting important misunderstandings in the recent literature, but on the substantive and methodological insights generated by this exchange, which are of broader interest to applied researchers.
AUTHORS: Kilian, Lutz
Following the 2009 L'Aquila earthquake, financing of reconstruction by the Italian central government resulted in a sharp and unanticipated discontinuity in grants across municipalities that were ex-ante very similar. Using the emergency financing law as an instrument, we identify the causal effect of municipal government spending on local activity, controlling for the negative supply shock from the earthquake. In our estimates, this "reconstruction multiplier" is around unity, and we show that the grants provided public insurance. Economic activity contracted in municipalities that did not receive the grants, while it expanded--or at least did not contract--in municipalities that did receive them. Our results suggest several policy implications with respect to the allocation mechanism of such grants.
AUTHORS: Porcelli, Francesco; Trezzi, Riccardo
Evidence on the Production of Cognitive Achievement from Moving to Opportunity
This paper performs a subgroup analysis on the effect of receiving a Moving to Opportunity (MTO) housing voucher on test scores. I find evidence of heterogeneity by number of children in the household in Boston, gender in Chicago, and race/ethnicity in Los Angeles. To study the mechanisms driving voucher effect heterogeneity, I develop a generalized Rubin Causal Model and propose an estimator to identify transition-specific Local Average Treatment Effects (LATEs) of school and neighborhood quality. Although I cannot identify such LATEs with the MTO data, the analysis demonstrates that membership in a specific demographic group is more predictive of voucher effects than is the group?s average change in school or neighborhood quality. I discuss some possible explanations.
AUTHORS: Aliprantis, Dionissi
Identifying Structural VARs with a Proxy Variable and a Test for a Weak Proxy
This paper develops a simple estimator to identify structural shocks in vector autoregressions (VARs) by using a proxy variable that is correlated with the structural shock of interest but uncorrelated with other structural shocks. When the proxy variable is weak, modeled as local to zero, the estimator is inconsistent and converges to a distribution. This limiting distribution is characterized, and the estimator is shown to be asymptotically biased when the proxy variable is weak. The F statistic from the projection of the proxy variable onto the VAR errors can be used to test for a weak proxy variable, and the critical values for different VAR dimensions, levels of asymptotic bias, and levels of statistical significance are provided. An important feature of this F statistic is that its asymptotic distribution does not depend on parameters that need to be estimated.
AUTHORS: Lunsford, Kurt Graden
Robust inference in models identified via heteroskedasticity
Identification via heteroskedasticity exploits differences in variances across regimes to identify parameters in simultaneous equations. I study weak identification in such models, which arises when variances change very little or the variances of multiple shocks change close to proportionally. I show that this causes standard inference to become unreliable, outline two tests to detect weak identification, and establish conditions for the validity of nonconservative methods for robust inference on an empirically relevant subset of the parameter vector. I apply these tools to monetary policy shocks, identified using heteroskedasticity in high frequency data. I detect weak identification in daily data, causing standard inference methods to be invalid. However, using intraday data instead allows the shocks to be strongly identified.
AUTHORS: Lewis, Daniel J.
The Econometrics of Oil Market VAR Models
Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact in the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between alternative oil market models, let alone the basis for the sometimes divergent conclusions reached in the literature. The purpose of this survey is to provide a guide to this literature. Our focus is on the econometric foundations of the analysis of oil market models with special attention to the identifying assumptions and methods of inference. We not only explain how the workhorse models in this literature have evolved, but also examine alternative oil market VAR models. We help the reader understand why the latter models sometimes generated unconventional, puzzling or erroneous conclusions. Finally, we discuss the construction of extraneous measures of oil demand and oil supply shocks that have been used as external or internal instruments for VAR models.
AUTHORS: Kilian, Lutz; Zhou, Xiaoqing