Showing papers by "Federal Reserve Bank of Dallas published in 2019"

Refining the workhorse oil market model

Abstract: The Kilian and Murphy (Journal of Applied Econometrics, 2014, 29, 454–478) structural vector autoregressive model has become the workhorse model for the analysis of oil markets. I explore various refinements and extensions of this model, including the effects of (1) correcting an error in the measure of global real economic activity, (2) explicitly incorporating narrative sign restrictions into the estimation, (3) relaxing the upper bound on the impact price elasticity of oil supply, (4) evaluating the implied posterior distribution of the structural models, and (5) extending the sample. I demonstrate that the substantive conclusions of Kilian and Murphy (2014) are largely unaffected by these changes.

The Rising Value of Time and the Origin of Urban Gentrification

Abstract: In the past decades, gentrification has transformed American central city neighborhoods. In this paper, I estimate a spatial equilibrium model to show that the rising value of high-skilled workers' time contributes to the gentrification of American central cities. I show that the increasing value of time raises the cost of commuting and exogenously increases the demand for central locations by high-skilled workers. While change in value of time has a modest direct effect on gentrification of the central cities, the effect is substantially magnified by endogenous amenity improvement driven by the changes in local skill mix.

A Cross-Sectional Machine Learning Approach for Hedge Fund Return Prediction and Selection

Abstract: We apply four machine learning methods to cross-sectional return prediction for hedge fund selection. We equip the forecast model with a set of idiosyncratic features, which are derived from historical returns of a hedge fund and capture a variety of fund-specific information. Evaluating the out-of-sample performance, we find that our forecast method significantly outperforms the four styled HFR Indices in almost all situations. Among the four machine learning methods, we find that deep neural network appears to be overall most effective. Investigating the source of methodological advantage of our method using a case study, we find that cross-sectional forecast outperforms forecast based on time series regression in most cases. Advanced modeling capabilities of machine learning further enhance these advantages. We find that the return-based features lead to higher returns than the benchmark of a set of macro-derivative features, and our forecast method yields best performance when the two sets of features are combined.

Real estate and the great crisis: lessons for macroprudential policy

Abstract: From a broad macro-financial structure perspective, overly easy credit conditions gave rise to house price booms and busts in several advanced economies (e.g., Ireland, Spain, and the U.S.), and, more specifically in the U.S., an underpricing of risk made possible by regulatory arbitrage and shadow financing fueled the credit and twin real estate bubbles of the mid-2000s. Across countries and over time bubbles have been particularly acute in real estate markets reflecting not only the relatively inelastic supply of land and thin trading of real estate, but also the amplification of shocks via backward-looking price expectations and the funding of consumption off distorted and elevated prices. The macro-prudential lessons from the Great Crisis highlight the need to prevent the build-up of excess real estate financing and limit the amplification and correlation of real estate risks. And progress has been made in each of these areas through imposing tougher or new restrictions on the choice sets of lenders or of borrowers, with particulars varying across advanced economies. While regulatory reform of banking is going forward, significant challenges remain especially in dealing with correlated risks associated with securitization.

Does drawing down the US Strategic Petroleum Reserve help stabilize oil prices

Abstract: We study the effects of releases from the US Strategic Petroleum Reserve (SPR) within the context of fully specified models of the global oil market that explicitly allow for storage demand as well as unanticipated changes in the SPR. We show that historically SPR policy interventions, defined as sequences of exogenous SPR shocks during selected periods, have helped stabilize the price of oil. Their effect on the price of oil, however, has been modest. For example, the cumulative effect of the SPR releases after the invasion of Kuwait in 1990 was a reduction of $2 per barrel in the real price of oil after 7 months. Whereas emergency drawdowns tend to lower the real price of oil, we find that exchanges tend to raise the real price of oil in the long run. We also provide a detailed analysis of the benefits of the 2018 White House proposal to sell off half of the SPR within the next decade. We show that the expected fiscal benefits of this plan are somewhat higher than the revenue of $16.6 billion dollars projected by the White House.

The Effects of the Volcker Rule on Corporate Bond Trading: Evidence from the Underwriting Exemption

Abstract: Using a novel within-dealer, within-security identification strategy, we examine intended and unintended effects of the Volcker rule on covered firms' corporate bond trading using dealer-identified regulatory data. We use the underwriting exemption to isolate the Volcker rule's effects separate from other post-crisis changes in bank regulation and broader trends in market liquidity. We find no evidence of the rule's intended reduction in the riskiness of covered firms' trading in corporate bonds. We find significant adverse liquidity effects on covered firms' corporate bond trading with 20-45 basis points higher costs for customers even for roundtrip trades of shorter duration. These effects do not appear to be transitional. The Volcker rule appears to have increased the cost of the liquidity provided by covered firms and has not decreased the liquidity risk exposure of covered firms. Finally, the Volcker rule has decreased the market share of covered firms. Customers appear to be trading more with non-bank dealers, who are exempt from the Volcker rule but also lack access to emergency liquidity support at the Fed's discount window.

Interest Rates and Insurance Company Investment Behavior

Abstract: Life insurance companies, the largest institutional holders of corporate bonds, tilt their portfolios towards higher-yield bonds when interest rates decline. This tilt seems to be primarily driven by an increase in duration rather than credit risk and insurers do not seem to increase the credit risk of their bonds as interest rates decline. Moreover, the duration gap between their assets and liabilities deviates from zero for extended periods of time in either direction. These patterns cannot be explained by incentives to reach for yield. We propose a new model of duration-matching under adjustment costs that conforms with these patterns and test other implications of this model. The gradual duration matching poses financial stability challenges distinct from reaching for yield.

A statistical learning approach for stock selection in the Chinese stock market

Abstract: Forecasting stock returns is extremely challenging in general, and this task becomes even more difficult given the turbulent nature of the Chinese stock market. We address the stock selection process as a statistical learning problem and build cross-sectional forecast models to select individual stocks in the Shanghai Composite Index. Decile portfolios are formed according to rankings of the forecasted future cumulative returns. The equity market’s neutral portfolio—formed by buying the top decile portfolio and selling short the bottom decile portfolio—exhibits superior performance to, and a low correlation with, the Shanghai Composite Index. To make our strategy more useful to practitioners, we evaluate the proposed stock selection strategy’s performance by allowing only long positions, and by investing only in A-share stocks to incorporate the restrictions in the Chinese stock market. The long-only strategies still generate robust and superior performance compared to the Shanghai Composite Index. A close examination of the coefficients of the features provides more insights into the changes in market dynamics from period to period.

Do Immigrants Threaten US Public Safety

Abstract: Executive SummaryOpponents of immigration often claim that immigrants, particularly those who are unauthorized, are more likely than US natives to commit crimes and that they pose a threat to publi...

Estimation of impulse response functions when shocks are observed at a higher frequency than outcome variables

Abstract: This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable), (iii) the data generating process (DGP) is given by a VAR model at the frequency of the shock, and (iv) the full set of relevant endogenous variables entering the DGP is unknown or unobserved. Consistency and asymptotic normality of the proposed MFDL estimators is established, and their small-sample performance is documented by a set of Monte Carlo experiments. The proposed approach is then applied to estimate the daily pass-through of changes in crude oil prices observed at the daily frequency to U.S. gasoline consumer prices observed at the weekly frequency. We find that the pass-through is fast, with about 23% of the crude oil price changes passed through to retail gasoline prices within five working days, representing about 42% of the long-run pass-through. JEL Classification: C22

Good Policies or Good Luck? New Insights on Globalization and the International Monetary Policy Transmission Mechanism

Abstract: The open-economy dimension is central to the discussion of the trade-offs that monetary policy faces in an increasingly integrated world. I investigate the monetary policy transmission mechanism in a two-country workhorse New Keynesian model where policy is set according to Taylor (in: Carnegie-Rochester conference series on public policy, vol 39, pp. 195–214, 1993) rules. I find that a common monetary policy isolates the effects of trade linkages on the cross-country dispersion alone, and that the establishment of a currency union as a means of deepening policy integration may lead to indeterminacy. I argue that the common (coordinated) monetary policy equilibrium is the relevant benchmark for policy analysis showing that open economies tend to experience lower macro volatility, a flatter Phillips curve, and more accentuated trade-offs between inflation and slack. Moreover, the trade elasticity often magnifies the effects of trade integration (globalization) beyond what conventional measures of trade openness would imply. I also discuss how other features such as the strength of a common anti-inflation bias in policymaking, technological diffusion across countries, and the sensitivity of labor supply to real wages influence the quantitative effects of policy and openness in this context. Finally, I conclude that these theoretical predictions are largely consistent with the stylized facts of the Great Moderation.

Facts and Fiction in Oil Market Modeling

Abstract: 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.

The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis

Abstract: This paper examines point and density forecasts from the European Central Bank’s Survey of Professional Forecasters. We derive individual uncertainty measures along with individual point- and density-based measures of disagreement. We also explore the relationship between uncertainty and disagreement, as well as their roles in respondents’ forecast performance and forecast revisions. We observe substantial heterogeneity in respondents’ uncertainty and disagreement. In addition, there is little co-movement between uncertainty and disagreement, and forecast performance shows a more robust inverse relationship with disagreement than with uncertainty. Further, forecast revisions display a more meaningful association with disagreement than with uncertainty: Those respondents displaying higher levels of disagreement revise their point and density forecasts by a larger amount.

Unintended Consequences of Credit Constraints on Housing: The Case of LTV Limits

Abstract: This paper examines the effects of a Loan-to-Value (LTV) limit on household's choices in the credit and housing markets. Using a large and novel micro database from Israel, including rich information on the loans, the borrowers and the acquired assets, and using matching techniques, I find that the LTV limit had an effect on the mortgage contract terms, but did not lead to credit rationing (no segment of the population is excluded from the market). The LTV limit induced borrowers to buy cheaper and lower quality assets and to move farther from high demand areas to lower quality neighborhoods. I conclude that the LTV limit, the most common macroprudentail policy tool, has an impact not only from a financial stability perspective, by reducing the leverage of households, but also has unintended consequences on borrower's choices in the housing market.

Are the Largest Banking Organizations Operationally More Risky

Abstract: This study demonstrates that, among large U.S. bank holding companies (BHCs), the largest ones are exposed to more operational risk. Specifically, they have higher operational losses per dollar of total assets, a result largely driven by the BHCs' failure to meet professional obligations to clients and/or faulty product design. Operational risk at the largest U.S. institutions is also found to: (i) be particularly persistent, (ii) have a counter-cyclical component (higher losses occur during economic downturns), and (iii) materialize through more frequent tail-risk events. We illustrate two plausible channels of BHC size that contribute to operational risk -- institutional complexity and moral hazard incentives arising from "too-big-to-fail." Our findings have important implications for large banking organization performance, risk, and supervision.

Drug-related violence in Mexico and its effects on employment

Abstract: This paper examines the effects of drug-related crimes on employment in Mexico at the state level during the period 2005–2014. Results indicate that such crimes have a negative impact on employment. We are able to decompose employment into low-skilled and high-skilled employment, and results are heterogeneous among both types of employment. Results indicate that a 10% increase in drug-related crimes reduces total employment up to 0.9%. Additionally, our empirical findings indicate that high-skilled employment is more sensitive to an increase in drug-related violence than low-skilled employment. Low-skilled employment decreases up to 0.3%, while skilled employment declines up to 1.5% when drug-related violence increases by 10%. It is also found that skilled employment responds at an increasing rate when drug violence skyrockets. We also find that a rise in drug-related crimes increases wages as a mechanism to retain jobs in violent places.

Uncertainty and Labor Market Fluctuations

Abstract: We investigate how a macroeconomic uncertainty shock affects the labor market. We focus on the uncertainty transmission mechanism, for which we employ a set of worker flow indicators in addition to labor stock variables. We incorporate common factors from such indicators into a framework that can simultaneously estimate historical macroeconomic uncertainty and its impacts on the macroeconomy and labor market. We find firms defer hiring as the real option value of waiting increases. Moreover, significantly more workers are laid off while voluntary quits drop, suggesting other mechanisms such as the aggregate demand channel play a crucial role.

Estimation of Impulse Response Functions When Shocks Are Observed at a Higher Frequency Than Outcome Variables

Abstract: This article proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is...

Employment Among US Hispanics: a Tale of Three Generations

Abstract: Immigrants’ descendants typically assimilate toward mainstream social and economic outcomes across generations. Hispanics in the USA are a possible exception to this pattern. Although there is a growing literature on intergenerational progress, or lack thereof, in education and earnings among Hispanics, there is little research on employment differences across immigrant generations. Using data from 1996 to 2017, this study reveals considerable differences in Hispanics’ employment rates across immigrant generations. Hispanic immigrant men tend to have higher employment rates than non-Hispanic whites and second- and third-plus generation Hispanics. Hispanic immigrant women have much lower employment rates, but employment rates rise considerably in the second generation. Nonetheless, US-born Hispanic women are less likely to work than non-Hispanic white women. The evidence thus suggests segmented assimilation, in which the descendants of Hispanic immigrants have worse outcomes across generations. While relatively low education levels do not appear to hamper Hispanic immigrants’ employment, they play a key role in explaining low levels of employment among Hispanic immigrants’ descendants. Race and selective ethnic attrition may also contribute to some of the patterns uncovered here.