Fiscal Stabilization and the Credibility of the U.S. Budget Sequestration Spending Austerity
Ruiyang Hu, Carlos E. Zarazaga
Abstract: Fiscal imbalances predating the Great Recession but aggravated by it prompted the U.S. Congress to enact in 2011 legislation that, in the absence of other measures, would trigger two years later a so-called “budget sequestration” procedure that implied reducing government discretionary spending to unprecedented low levels over the following decade. For that reason, economic agents may not have expected this “fiscal stabilization measure of last resort” to be sustainable when it was put into effect in 2013 as scheduled. This is exactly the issue this paper set out to explore, on the grounds that sizing up the expectations that economic agents had about the budget sequestration can provide powerful insights on how fiscal stabilization is likely to proceed in the U.S., going forward. The paper makes inferences about the credibility enjoyed by the budget sequestration with an adapted version of the Business Cycle Accounting approach, originally developed for other purposes. The main finding is that the evidence favors a scenario in which spending cuts are half the size of those actually implied by the sequester. The paper takes this result as an indication that the U.S. is unlikely to address its unresolved fiscal imbalances with just spending austerity, an interpretation consistent with existing literature that traces the seemingly anomalous behavior of economic variables during the Great Recession and its aftermath to alternative fiscal stabilization mechanisms.
What Drives Economic Policy Uncertainty in the Long and Short Runs? European and U.S. Evidence over Several Decades
John V. Duca, Jason L. Saving
Abstract: Economic policy uncertainty (EPU) has increased markedly in recent years in the U.S. and Europe, and some have posited a link between this phenomenon and subpar economic growth in advanced economies (see Baker, Bloom, and Davis, 2015). But methodological and data concerns have thus far raised doubts about whether EPU contains marginal and exogenous information about other economic phenomena. Our work analyzes the impact on EPU of several possibly endogenous variables, such as inflation and unemployment rates in countries where EPU is measured. We also consider longer-term technological factors, such as media fragmentation, which by undermining political consensus may indirectly elevate EPU. We find that about 40 percent of EPU movements can be explained by long- and short-run movements in these determinants, which is consistent with limited evidence that de-trended movements in EPU may contain marginal information about GDP growth and other macro variables.
What Drives Commodity Price Booms and Busts?
David S. Jacks, Martin Stuermer
Abstract: What drives commodity price booms and busts? We provide evidence on the dynamic effects of commodity demand shocks, commodity supply shocks, and inventory demand shocks on real commodity prices. In particular, we analyze a new data set of price and production levels for 12 agricultural, metal, and soft commodities from 1870 to 2013. We identify differences in the type of shock driving prices of the various types of commodities and relate these differences to commodity types which reflect differences in long-run elasticities of supply and demand. Our results show that demand shocks strongly dominate supply shocks.
The Roles of Inflation Expectations, Core Inflation, and Slack in Real-Time Inflation Forecasting
N. Kundan Kishor, Evan F. Koenig
Abstract: Using state-space modeling, we extract information from surveys of long-term inflation expectations and multiple quarterly inflation series to undertake a real-time decomposition of quarterly headline PCE and GDP-deflator inflation rates into a common long-term trend, common cyclical component, and high-frequency noise components. We then explore alternative approaches to real-time forecasting of headline PCE inflation. We find that performance is enhanced if forecasting equations are estimated using inflation data that have been stripped of high-frequency noise. Performance can be further improved by including an unemployment-based measure of slack in the equations. The improvement is statistically significant relative to benchmark autoregressive models and also relative to professional forecasters at all but the shortest horizons. In contrast, introducing slack into models estimated using headline PCE inflation data or conventional core inflation data causes forecast performance to deteriorate. Finally, we demonstrate that forecasting models estimated using the Kishor-Koenig (2012) methodology-which mandates that each forecasting VAR be augmented with a flexible state-space model of data revisions-consistently outperform the corresponding conventionally estimated forecasting models.
Forward Guidance and the State of the Economy
Benjamin D. Keen, Alexander W. Richter, Nathaniel A. Throckmorton
Abstract: This paper examines forward guidance using a nonlinear New Keynesian model with a zero lower bound (ZLB) constraint on the nominal interest rate. Forward guidance is modeled with news shocks to the monetary policy rule. The effectiveness of forward guidance depends on the state of the economy, the speed of the recovery, the ZLB constraint, the degree of uncertainty, the monetary response to inflation, the size of the news shocks, and the forward guidance horizon. Specifically, the stimulus from forward guidance falls as the economy deteriorates or as households expect a slower recovery. When the ZLB binds, less uncertainty about the economy or an expectation of a stronger response to inflation reduces the benefit of forward guidance. Forward guidance via a news shock is less stimulative than an unanticipated monetary policy shock around the steady state, but a news shock is more stimulative near the ZLB and always has a larger cumulative effect on output. When the central bank extends the forward guidance horizon, the cumulative effect initially increases but then decreases. These results indicate that there are limits to the stimulus forward guidance can provide, but that stimulus is largest when the news is communicated early in a recession.
Estimating Taxable Income Responses with Elasticity Heterogeneity
Anil Kumar, Che-Yuan Liang
Abstract: We explore the implications of heterogeneity in the elasticity of taxable income (ETI) for tax-reform based estimation methods. We theoretically show that existing methods yield elasticities that are biased and lack policy relevance. We illustrate the empirical importance of our theoretical analysis using the NBER tax panel for 1979-1990. We show that elasticity heterogeneity is the main explanation for large differences between estimates in the previous literature. Our preferred, newly suggested method yields elasticity estimates of approximately 0.7 for taxable income and 0.2 for broad income.
Targeted Search in Matching Markets PDF
Anton Cheremukhin, Paulina Restrepo-Echavarria, Antonella Tutino
Abstract: We endogenize the degree of randomness in the matching process by proposing a model where agents have to pay a search cost to locate potential matches more accurately. The model features a tension between an agent’s desire to find a more productive match and to maximize the odds of finding a match. This tension drives a wedge between the shape of sorting patterns and the shape of the underlying match payoff function. We show the empirical relevance of the latter prediction by applying the model to the U.S. marriage market.
Student Loan Relief Programs: Implications for Borrowers and the Federal Government
Wenhua Di, Kelly D. Edmiston
Abstract: As college costs increase and more students fund their education through borrowing, debt load and delinquency rates have become significant problems on a number of levels. Student loan obligations are challenging to manage for new graduates with lower earnings and borrowers in financial hardship. This paper discusses the federal student loan repayment relief programs that are available and estimates their borrower and fiscal impacts. The implications of relief plans on borrowers’ costs and the federal budget vary for different loan amounts, income levels, and relief program.
It is challenging for policymakers to design programs that adequately balance the risks between borrowers and taxpayers. Existing programs are also tremendously complicated, making it difficult for borrowers to make informed decisions on repayment programs. This paper examines how the various programs work in practice and considers their likely outcomes over a set of income-debt-program scenarios to bring much needed clarity to the repayment environment. In our analysis, lower-income borrowers and borrowers who will have significant remaining balance forgiven at the end of the required repayment period are generally more likely to benefit from student loan relief programs, but participation of these borrowers can be very costly from a fiscal perspective.
Residual Seasonality in U.S. GDP Data
Keith R. Phillips, Jack Wang
Abstract: Rudebush et al (2015a, b) and the Bureau of Economic Analysis find the presence of residual seasonality in the official estimates of U.S. real gross domestic product (GDP). Directly seasonally adjusting official seasonally adjusted GDP, which we refer to as double seasonal adjustment, could revise the first quarter growth in the past several years upward by an average of about 1.5 percentage points. The presence of residual seasonality can significantly distort current analysis of national and regional economies. In this paper we look more closely at the U.S. GDP data and study the quality of the seasonal adjustment when it is applied to data that has already been indirectly seasonally adjusted. We find that double seasonal adjustment can lead to estimates that are of moderate quality. While the optimal method would be to directly seasonally adjust the aggregate not seasonally adjusted data, if this is not possible, double seasonally adjusted data would likely lead to better estimates.
The Rank Effect for Commodities
Ricardo T. Fernholz, Christoffer Koch
Abstract: We uncover a large and significant low-minus-high rank effect for commodities across two centuries. There is nothing anomalous about this anomaly, nor is it clear how it can be arbitraged away. Using nonparametric econometric methods, we demonstrate that such a rank effect is a necessary consequence of a stationary relative asset price distribution. We confirm this prediction using daily commodity futures prices and show that a portfolio consisting of lower-ranked, lower-priced commodities yields 23% higher annual returns than a portfolio consisting of higher-ranked, higher-priced commodities. These excess returns have a Sharpe ratio nearly twice as high as the U.S. stock market yet are uncorrelated with market risk. In contrast to the extensive literature on asset pricing factors and anomalies, our results are structural and rely on minimal and realistic assumptions for the long-run properties of relative asset prices.
Are Nonlinear Methods Necessary at the Zero Lower Bound?
Alexander W. Richter, Nathaniel A. Throckmorton
Abstract: This paper examines the importance of the zero lower bound (ZLB) constraint on the nominal interest rate by estimating three variants of a small-scale New Keynesian model: (1) a nonlinear model with an occassionally binding ZLB constraint; (2) a constrained linear model, which imposes the constraint in the filter but not the solution; and (3) an unconstrained linear model, which never imposes the constraint. The posterior distributions are similar, but important differences arise in their predictions at the ZLB. The nonlinear model fits the data better at the ZLB and primarily attributes the ZLB to a reduction in household demand due to discount factor shocks. In the linear models, the ZLB is due to large contractionary monetary policy shocks, which is at odds with the Fed’s expansionary policy during the Great Recession. Posterior predictive analysis shows the nonlinear model is partially able to account for the increase in output volatility and the negative skewness in output and inflation that occurred during the ZLB period, whereas the linear models predict almost no changes in those statistics. We also compare the results from our nonlinear model to the quasi-linear solution based on OccBin. The quasi-linear model fits the data better than the linear models, but it still generate too little volatility at the ZLB and predicts that a large policy shock caused the ZLB to bind in 2008Q4.
Economic Policy Uncertainty and the Credit Channel: Aggregate and Bank Level U.S. Evidence over Several Decades
Michael D. Bordo, John V. Duca and Christoffer Koch
Abstract: Economic policy uncertainty affects decisions of households, businesses, policy makers and financial intermediaries. We first examine the impact of economic policy uncertainty on aggregate bank credit growth. Then we analyze commercial bank entity level data to gauge the effects of policy uncertainty on financial intermediaries' lending. We exploit the cross-sectional heterogeneity to back out indirect evidence of its effects on businesses and households. We ask (i) whether, conditional on standard macroeconomic controls, economic policy uncertainty affected bank level credit growth, and (ii) whether there is variation in the impact related to banks' balance sheet conditions; that is, whether the effects are attributable to loan demand or, if impact varies with bank level financial constraints, loan supply. We find that policy uncertainty has a significant negative effect on bank credit growth. Since this impact varies meaningfully with some bank characteristics - particularly the overall capital-to-assets ratio and bank asset liquidity-loan supply factors at least partially (and significantly) help determine the influence of policy uncertainty. Because other studies have found important macroeconomic effects of bank lending growth on the macroeconomy, our findings are consistent with the possibility that high economic policy uncertainty may have slowed the U.S. economic recovery from the Great Recession by restraining overall credit growth through the bank lending channel.
Why Are Big Banks Getting Bigger?
Ricardo T. Fernholz and Christoffer Koch
Abstract: The U.S. banking sector has become substantially more concentrated since the 1990s, raising questions about both the causes and implications of this consolidation. We address these questions using nonparametric empirical methods that characterize dynamic power law distributions in terms of two shaping factors — the reversion rates (a measure of crosssectional mean reversion) and idiosyncratic volatilities of assets for different size-ranked banks. Using quarterly data for subsidiary commercial banks and thrifts and their parent bank-holding companies, we show that the greater concentration of U.S. bank-holding company assets is a result of lower mean reversion, a result consistent with policy changes such as interstate branching deregulation and the repeal of Glass-Steagall. In contrast, the greater concentration of both U.S. commercial bank and thrift assets is a result of higher idiosyncratic volatility, yet, idiosyncratic volatility of parent bank-holding company assets fell. This contrast suggests that diversification through non-banking activities has reduced the idiosyncratic asset volatilities of the largest bank-holding companies and affected systemic risk.
Irregular Immigration in the European Union
Pia M. Orrenius and Madeline Zavodny
Abstract: Unauthorized immigration is on the rise again in the EU. Although precise estimates are hard to come by, proximity to nations in turmoil and the promise of a better life have drawn hundreds of thousands of irregular migrants to the EU in 2014-2015. Further complicating the ongoing challenge is the confounding flow of humanitarian migrants, who are fleeing not for a job but for their lives. Those who flee for better economic conditions are irregular migrants, not humanitarian migrants, but the lines between the two are often blurred. This policy brief surveys the state of irregular immigration to the EU and draws on lessons from the U.S. experience. It focuses on economic aspects of unauthorized immigration. There are economic benefits to receiving countries as well as to unauthorized migrants themselves, but those benefits require that migrants are able to access the labor market and that prices and wages are flexible. Meanwhile, mitigating fiscal costs requires limiting access to public assistance programs for newcomers. Successfully addressing irregular migration is likely to require considerable coordination and cost-sharing among EU member states.
Targeted Business Incentives and the Debt Behavior of Households
Wenhua Di and Daniel L. Millimet
Abstract: 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.
Why Does the FDIC Sue?
Christoffer Koch and Ken Okamura
Abstract: Cases the Federal Deposit Insurance Corporation (FDIC) pursues against the directors and officers of failed commercial banks for (gross) negligence are important for the corporate governance of U.S. commercial banks. These cases shape the kernel of bank corporate governance, as they guide expectations of bankers and regulators in defining the limits of acceptable behavior under financial distress. We examine the differences in behavior of all 408 U.S. commercial banks that were taken into receivership between 2007–2012. Sued banks had different balance sheet dynamics in the three years prior to failure. These banks were generally larger, faster growing, obtained riskier funding and were more “optimistic”. We find evidence that the behavior of bank boards adjusts in an out-of-sample set of banks. Our results suggest the FDIC does not only pursue “deep pockets”, but sets corporate governance standards for all banks by suing negligent directors and officers.
Capital Goods Trade, Relative Prices, and Economic Development
Piyusha Mutreja, B. Ravikumar and Michael Sposi
Abstract: International trade in capital goods has quantitatively important effects on economic development through two channels: capital formation and aggregate TFP. We embed a multi country, multi sector Ricardian model of trade into a neoclassical growth framework. Our model matches several trade and development facts within a unified framework: the world distribution of capital goods production and trade, cross-country differences in investment rate and price of final goods, and cross-country equalization of price of capital goods. Reducing barriers to trade capital goods allows poor countries to access more efficient means of capital goods production abroad, leading to relatively higher capital output ratios. Meanwhile, poor countries can specialize more in their comparative advantage—non-capital goods production—and increase their TFP. The income gap between rich and poor countries declines by 40 percent by eliminating barriers to trade capital goods.
A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models
Supplement 1 | Supplement 2
Alexander Chudik, George Kapetanios and M. Hashem Pesaran
Abstract: Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique used to trade off parsimony and fit when the number of possible covariates is large, often much larger than the number of available observations. However, issues such as the choice of a penalty function and tuning parameters associated with the use of penalized regressions remain contentious. In this paper, we provide an alternative approach that considers the statistical significance of the individual covariates one at a time, whilst taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time Multiple Testing (OCMT) procedure. The OCMT provides an alternative to penalised regression methods: It is based on statistical inference and is therefore easier to interpret and relate to the classical statistical analysis, it allows working under more general assumptions, it is faster, and performs well in small samples for almost all of the different sets of experiments considered in this paper. We provide extensive theoretical and Monte Carlo results in support of adding the proposed OCMT model selection procedure to the toolbox of applied researchers. The usefulness of OCMT is also illustrated by an empirical application to forecasting U.S. output growth and inflation.
Financial Performance and Macroeconomic Fundamentals in Emerging Market Economies over the Global Financial Cycle
Scott Davis and Andrei Zlate
Abstract: This paper explores the relationship between financial performance and macroeconomic fundamentals in emerging market economies not only in times of crises, but in general during crisis and non-crisis years over the global financial cycle. Using a panel framework with data for 119 emerging market economies at an annual frequency, we examine whether the relationship between performance and fundamentals varies in magnitude and/or switches sign between crisis and non-crisis years. We find that better macroeconomic fundamentals (such as a stronger net foreign asset positions and higher stocks of foreign exchange reserves) are associated with better financial performance not just during crisis episodes, but also during normal times. Quantitatively, the impact of fundamentals on performance is smaller during normal times than during crisis years, but works in the same direction and is statistically significant. The results are consistent with those of recent empirical studies on the link between financial performance and fundamentals during episodes of global financial stress, but generalizes the results to the global financial cycle.
Macroeconomic News and Asset Prices Before and After the Zero Lower Bound
Christoffer Koch and Julieta Yung
Abstract: With short-term policy interest rates constrained by their effective zero lower bound (ZLB), monetary policy relied on communicating the future path of policy conditional on incoming macroeconomic data. Motivated by this, we exploit intra-day prices to investigate how updates on the state of the U.S. economy affect interest rates and exchange rates before and after the ZLB. We find that releases reflecting the dual mandate of the Fed rose in importance and – as an ex-post acknowledgement of the sources of the Great Recession – additional housing market indicators and GDP revisions, that hitherto left markets unaffected, became market movers.
System Reduction and Finite-Order VAR Solution Methods for Linear Rational Expectations Models
Abstract: This paper considers the solution of a large class of linear rational expectations (LRE) models and its characterization via finite-order VARs. The solution of the canonical LRE model can be cast in state-space form and solved for by the method of undetermined coefficients. In this paper I propose an approach that simplifies the systematic characterization of the solution into finite-order VAR form and checks existence and uniqueness based on the solution of a companion Sylvester equation. Solving LRE models with a finite-order VAR representation via the Sylvester equation is straightforward to implement, efficient, and can be handled easily with standard matrix algebra. An application to the workhorse New Keynesian model with accompanying Matlab codes is provided to illustrate the implementation of the procedure in practice.
Diversification and Specialization of U.S. States | Codes
Janet Koech and Mark A. Wynne
Abstract: This paper documents the evolution of the international relationships of individual U.S. states along three dimensions: trade, migration, and finance. We examine how specialized or diversified state economies differ in terms of the products they export and with whom they trade, the origins of the immigrants who live in the state, and the origins of the foreign banks operating in the state. We show that states that are diversified along one of these dimensions are often quite specialized along others. New York is–perhaps, not surprisingly–the most diversified state in terms of global linkages.
Central Bank Communications: A Case Study
J.Scott Davis and Mark A. Wynne
Abstract: Over the past twenty five years, central bank communications have undergone a major revolution. Central banks that previously shrouded themselves in mystery now embrace social media to get their message out to the widest audience. The Federal Reserve System has not always been at the forefront of these changes, but the volume of information about monetary policy that the Federal Open Market Committee (FOMC) now releases dwarfs what it was releasing a quarter century ago. In this paper we focus on just one channel of FOMC communications, the post-meeting statement. We document how it has evolved over time, and in particular the extent to which it has become more detailed, but also more difficult to understand. We then use a VAR with daily financial market data to estimate a daily time series of U.S. monetary policy shocks. We show how these shocks on Fed statement release days have gotten larger as the statement has gotten longer and more detailed, and we show that the length and complexity of the statement has a direct effect on the size of the monetary policy shock following a Fed decision.
Half-Panel Jackknife Fixed Effects Estimation of Panels with Weakly Exogenous Regressors
Supplement | Codes
Alexander Chudik, M. Hashem Pesaran and Jui-Chung Yang
Abstract: This paper considers estimation and inference in fixed effects (FE) panel regression models with lagged dependent variables and/or other weakly exogenous (or predetermined) regressors when N(the cross section dimension) is large relative to T (the time series dimension). The paper first derives a general formula for the bias of the FE estimator which is a generalization of the Nickell type bias derived in the literature for the pure dynamic panel data models. It shows that in the presence of weakly exogenous regressors, inference based on the FE estimator will result in size distortions unless N / T is sufficiently small. To deal with the bias and size distortion of FE estimator when N is large relative to T, the use of half-panel Jackknife FE estimator is proposed and its asymptotic distribution is derived. It is shown that the bias of the proposed estimator is of order T -2, and for valid inference it is only required that N / T 3 0, as N, T jointly. Extensions to panel data models with time effects (TE), for balanced as well as unbalanced panels, are also provided. The theoretical results are illustrated with Monte Carlo evidence. It is shown that the FE estimator can suffer from large size distortions when N > T, with the proposed estimator showing little size distortions. The use of half-panel jackknife FE-TE estimator is illustrated with two empirical applications from the literature.
Exposure to International Crises: Trade vs. Financial Contagion
Abstract: I identify new patterns in countries' economic performance over the 2007-2014 period based on proximity through distance, trade, and finance to the US subprime mortgage and Eurozone debt crisis areas. To understand the causes of the cross-country variation, I develop an open economy model with two transmission channels that can be shocked separately: international trade and finance. The model is the first to include a government and heterogeneous firms that can default independently of one another and has a novel endogenous cost of sovereign default. I calibrate the model to the average experiences of countries near to and far from the crisis areas. Using these calibrations, disturbances on the order of those observed during the late 2000s are separately applied to each channel to study transmission. The results suggest credit disruption as the primary contagion driver, rather than the trade channel. Given the substantial degree of financial contagion, I run a series of counterfactuals studying the efficacy of capital controls and find that they would be a useful tool for preventing similarly severe contagion in the future, so long as there is not capital immobility to the degree that the local sovereign can default without suffering capital flight.
The Market Resources Method for Solving Dynamic Optimization Problems
Ayşe Kabukçuoğlu and Enrique Martínez-García
Abstract: We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll’s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides advantages in terms of speed and accuracy over Howard’s policy improvement algorithm. Codes are available.
Big Data Analytics: A New Perspective
Supplement 1 | Supplement 2
A. Chudik, G. Kapetanios and M. H. Pesaran
Abstract: Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised regression has become the de facto benchmark technique used to trade off parsimony and fit when the number of possible covariates is large, often much larger than the number of available observations. However, issues such as the choice of a penalty function and tuning parameters associated with the use of penalised regressions remain contentious. In this paper, we provide an alternative approach that considers the statistical significance of the individual covariates one at a time, whilst taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time Multiple Testing (OCMT) procedure. The OCMT has a number of advantages over the penalised regression methods: It is based on statistical inference and is therefore easier to interpret and relate to the classical statistical analysis, it allows working under more general assumptions, it is computationally simple and considerably faster, and it performs better in small samples for almost all of the five different sets of experiments considered in this paper. Despite its simplicity, the theory behind the proposed approach is quite complicated. We provide extensive theoretical and Monte Carlo results in support of adding the proposed OCMT model selection procedure to the toolbox of applied researchers.
Economic Fundamentals and Monetary Policy Autonomy
Abstract: During a time of rising world interest rates, the central bank of a small open economy may be motivated to increase its own interest rate to keep from suffering a destabilizing outflow of capital and depreciation in the exchange rate. This is especially true for a small open economy with a current account deficit, which relies on foreign capital inflows to finance this deficit. This paper will investigate the underlying structural characteristics that would lead an economy with a floating exchange rate to adjust their interest rate in line with the foreign interest rate, and thus adopt a de facto exchange rate ”peg”. Using a panel data regression similar to that in Shambaugh (QJE 2004) and most recently in Klein and Shambaugh (AEJ Macro 2015), this paper shows that the method of current account financing has a large effect on whether or not the central bank will opt for exchange rate and capital flow stabilization during a time of rising world interest rates. A current account deficit financed mainly through reserve depletion or the accumulation of private sector debt will cause the central bank to pursue de facto exchange rate stabilization, whereas a current account deficit financed through equity or FDI will not. Quantitatively, reserve depletion of about 7% of GDP will motivate the central bank with a floating currency to adjust its interest rate in line with the foreign interest rate to where it appears that the central bank has an exchange rate peg.
Wages and Human Capital in Finance: International Evidence, 1970-2005
Hamid Boustanifar, Everett Grant and Ariell Reshef
Abstract: We study the allocation and compensation of human capital in the finance industry in a set of developed economies in 1970-2005. Finance relative skill intensity and skilled wages generally increase but not in all countries, and to varying degrees. Skilled wages in finance account for 36% of increases in overall skill premia, although finance only accounts for 5.4% of skilled private sector employment, on average. Financial deregulation, financial globalization and bank concentration are the most important factors driving wages in finance. Differential investment in information and communication technology does not have causal explanatory power. High finance wages attract skilled international immigration to finance, raising concerns for "brain drain".
Quantitative Assessment of the Role of Incomplete Asset Markets on the Dynamics of the Real Exchange Rate
Abstract: I develop a two-country New Keynesian model with capital accumulation and incomplete international asset markets that provides novel insights on the effect that imperfect international risk-sharing has on international business cycles and RER dynamics. I find that business cycles appear similar whether international asset markets are complete or not when driven by a combination of non-persistent monetary shocks and persistent productivity (TFP) shocks. In turn, international asset market incompleteness has sizeable effects if (persistent) investment-specific technology (IST) shocks are a main driver of business cycles. I also show that the model with incomplete international asset markets can approximate the RER volatility and persistence observed in the data, for instance, if IST shocks are near-unitroot. Hence, I conclude that the nature of shocks, the extent of financial integration across countries and the existing limitations on asset trading are central to understand the dynamics of the real exchange rate and the endogenous international transmission over the business cycles.
Inflation as a Global Phenomenon—Some Implications for Policy Analysis and Forecasting
Ayşe Kabukçuoğlu and Enrique Martínez-García
Abstract: 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 (Martínez-García and Wynne (2010), Kabukcuoglu and Martínez-García (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.