Showing results 1 to 10 of approximately 10.(refine search)
Spatial Dependence and Data-Driven Networks of International Banks
This paper computes data-driven correlation networks based on the stock returns of international banks and conducts a comprehensive analysis of their topological properties. We first apply spatial-dependence methods to filter the effects of strong common factors and a thresholding procedure to select the significant bilateral correlations. The analysis of topological characteristics of the resulting correlation networks shows many common features that have been documented in the recent literature but were obtained with private information on banks? exposures. Our analysis validates these market-based adjacency matrices as inputs for the spatio-temporal analysis of shocks in the banking system.
AUTHORS: Craig, Ben R.; Saldias Zambrana, Martin
How have global shocks impacted the real effective exchange rates of individual Euro area countries since the Euro's creation?
This paper uncovers the response pattern to global shocks of euro area countries' real effective exchange rates before and after the start of Economic and Monetary Union (EMU), a largely open ended question when the euro was created. We apply to that end a newly developed methodology based on high dimensional VAR theory. This approach features a dominant unit to a large set of over 60 countries' real effective exchange rates and is based on the comparison of two estimated systems: one before and one after EMU. ; We find strong evidence that the pattern of responses depends crucially on the nature of global shocks. In particular, post-EMU responses to global US dollar shocks have become similar to Germany's response before EMU, i.e. to that of the economy that used to issue Europe's most credible legacy currency. ; By contrast, post-EMU responses of euro area countries to global risk aversion shocks have become similar to those of Italy, Portugal or Spain before EMU, i.e. of economies of the euro area's periphery. Our findings also suggest that the divergence in external competitiveness among euro area countries over the last decade, which is at the core of today's debate on the future of the euro area, is more likely due to country-specific shocks than to global shocks.
AUTHORS: Chudik, Alexander; Mehl, Arnaud; Bussiere, Matthieu
Inflation as a global phenomenon - some implications for policy analysis and forecasting
We evaluate the performance of inflation forecasts based on the open-economy Phillips curve by exploiting the spatial pattern of international propagation of inflation. We model these spatial linkages using global inflation and either domestic slack or oil price fluctuations, motivated by a novel interpretation of the forecasting implications of the workhorse openeconomy New Keynesian model (Martnez-Garca and Wynne (2010), Kabukcuoglu and Martnez-Garca (2014)). We find that incorporating spatial interactions yields significantly more accurate forecasts of local inflation in 14 advanced countries (including the U.S.) than a simple autoregressive model that captures only the temporal dimension of the inflation dynamics.
AUTHORS: Martinez-Garcia, Enrique; Kabukcuoglu, Ayse
Impact of Allowing Sunday Alcohol Sales in Georgia on Employment and Hours
This paper uses differential timing across counties of the removal of restrictions on Sunday alcohol sales in the state of Georgia to determine whether the change had an impact on employment and hours in the beer, wine, and liquor retail sales industry. A triple-difference (DDD) analysis finds significant relative increases in average weekly hours in the treated industry. There is no significant relative employment increase. The DDD hours result is stronger when we limit the counties removing restrictions to those that border states with significantly higher alcohol excise taxes.
AUTHORS: Hotchkiss, Julie L.; Qi, Yanling
Targeted business incentives and the debt behavior of households
The empirical effects of place-based tax incentive schemes designed to aid low-income communities are unclear. While a growing number of studies find beneficial effects on employment, there is little investigation into other behaviors of households affected by such programs. We analyze the impact of the Texas Enterprise Zone Program on household debt and delinquency. Specifically, we utilize detailed information on all household liabilities, delinquencies, and credit scores from the Federal Reserve Bank of New York Consumer Credit Panel/Equifax, a quarterly longitudinal 5% random sample of all individuals in the US with a social security number and a credit report. We identify the causal effect of the program by using a sharp regression discontinuity approach that exploits the known institutional rules of the program. We find a modest positive impact on the repayment of retail loans, and the evidence of an increase in the delinquency rates of auto loans, as well as in Chapter 13 bankruptcy filings.
AUTHORS: Millimet, Daniel; Di, Wenhua
Exploring the Nexus Between Inflation and Globalization Under Inflation Targeting Through the Lens of New Zealand’s Experience
We investigate empirically the inflation dynamics in New Zealand, a small open economy and a pioneer in inflation targeting, under various open-economy Phillips curve specifications. Our forecasting exercise suggests that open-economy Phillips curves under standard measures of global slack do not help forecast domestic inflation, possibly indicating measurement problems with global slack itself. In turn, under a stable inflation target we still find that (i) global inflation and (ii) global inflation and oil prices have information content for headline CPI and core CPI inflation over the 1997:Q3-2015:Q1 period and appear to be reliable proxies for global slack in forecasting inflation.
AUTHORS: Martinez-Garcia, Enrique; Kabukcuoglu, Ayse; Soytas, Mehmet A.
Assessing Macroeconomic Tail Risk
What drives macroeconomic tail risk? To answer this question, we borrow a definition of macroeconomic risk from Adrian et al. (2019) by studying (left-tail) percentiles of the forecast distribution of GDP growth. We use local projections (Jord, 2005) to assess how this measure of risk moves in response to economic shocks to the level of technology, monetary policy, and financial conditions. Furthermore, by studying various percentiles jointly, we study how the overall economic outlook-as characterized by the entire forecast distribution of GDP growth-shifts in response to shocks. We find that contractionary shocks disproportionately increase downside risk, independently of what shock we look at.
AUTHORS: Loria, Francesca; Matthes, Christian; Zhang, Donghai
Binscatter is very popular in applied microeconomics. It provides a flexible, yet parsimonious way of visualizing and summarizing ?big data? in regression settings, and it is often used for informal testing of substantive hypotheses such as linearity or monotonicity of the regression function. This paper presents a foundational, thorough analysis of binscatter: We give an array of theoretical and practical results that aid both in understanding current practices (that is, their validity or lack thereof) and in offering theory-based guidance for future applications. Our main results include principled number of bins selection, confidence intervals and bands, hypothesis tests for parametric and shape restrictions of the regression function, and several other new methods, applicable to canonical binscatter as well as higher-order polynomial, covariate-adjusted, and smoothness-restricted extensions thereof. In particular, we highlight important methodological problems related to covariate adjustment methods used in current practice. We also discuss extensions to clustered data. Our results are illustrated with simulated and real data throughout. Companion general-purpose software packages for Stata and R are provided. Finally, from a technical perspective, new theoretical results for partitioning-based series estimation are obtained that may be of independent interest.
AUTHORS: Farrell, Max H.; Cattaneo, Matias D.; Feng , Yingjie; Crump, Richard K.
Assessing Macroeconomic Tail Risk
What drives macroeconomic tail risk? To answer this question, we borrow a definition of macroeconomic risk from Adrian et al. (2019) by studying (left-tail) percentiles of the forecast distribution of GDP growth. We use local projections (Jord, 2005) to assess how this measure of risk moves in response to economic shocks to the level of technology, monetary policy, and financial conditions. Furthermore, by studying various percentiles jointly, we study how the overall economic outlook?as characterized by the entire forecast distribution of GDP growth?shifts in response to shocks. We find that contractionary shocks disproportionately increase downside risk, independently of what shock we look at.
AUTHORS: Loria, Francesca; Matthes, Christian; Zhang, Donghai
Shrinking Networks: A Spatial Analysis of Bank Branch Closures
As more consumers take advantage of online banking services, branch networks are declining across the country. Limited attention has been given to identifying any possible spatial patterns of branch closures and, more importantly, the community demographics where branches close their doors. This analysis uses an innovative spatial statistics concept to study financial services: Using data from 2010 to 2016, a random labelling test is conducted to understand branch closure clustering in the Philadelphia, Chicago, and Baltimore metropolitan statistical areas (MSAs). Additionally, spatial autocorrelation is tested, and an MSA-level spatial regression analysis is done to see if there is a pattern to branch closures in metropolitan areas. I find evidence of branch closure clusters in the Chicago and Philadelphia MSAs; however, this spatial pattern is only observable within the suburbs, not the primary city itself. Using a random labelling test is a methodological innovation in regional economic studies and propels our understanding of banking deserts and underserved neighborhoods.
AUTHORS: Tranfaglia, Anna