NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgement) should be cleared with the author(s) to protect the tentative character of these papers.

ABSTRACT Understanding the sensitivity of gasoline demand to changes in prices and income has important implications for policies related to climate change, optimal taxation and national security, to name only a few. While the short-run price and income elasticities of gasoline demand in the United States have been studied extensively, the vast majority of these studies focus on consumer behavior in the 1970s and 1980s. There are a number of reasons to believe that current demand elasticities differ from these previous periods, as transportation analysts have hypothesized that behavioral and structural factors over the past several decades have changed the responsiveness of U.S. consumers to changes in gasoline prices. In this paper, we compare the price and income elasticities of gasoline demand in two periods of similarly high prices from The estimated short-run income elasticities range from 0.21 to 0.75 and when estimated with the same models are not significantly different between the two periods. One implication of these findings is that gasoline taxes would need to be significantly larger today in order to achieve an equivalent reduction in gasoline consumption. This, coupled with the political difficulties in adopting gasoline taxes, suggests that policies and technologies designed to improve fuel economy are likely becoming relatively more attractive as a means to reduce fuel consumption.

This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of non-stationarity in the data. We refer to it as PANIC – a ‘Panel Analysis of Non-stationarity in Idiosyncratic and Common components’. PANIC consists of univariate and panel tests with a number of novel features. It can detect whether the nonstationarity is pervasive, or variable-specific, or both. It tests the components of the data instead of the observed series. Inference is therefore more accurate when the components have different orders of integration. PANIC also permits the construction of valid panel tests even when cross-section correlation invalidates pooling of statistics constructed using the observed data. The key to PANIC is consistent estimation of the components even when the regressions are individually spurious. We provide a rigorous theory for estimation and inference. In Monte Carlo simulations, the tests have very good size and power. PANIC is applied to a panel of inflation series.

To investigate how a fixed exchange rate affects monetary policy, this paper classifies countries as pegged or nonpegged and examines whether a pegged country must follow the interest rate changes in the base country. Despite recent research which hints that all countries, not just pegged countries, lack monetary freedom, the evidence shows that pegs follow base country interest rates more than nonpegs. This study uses actual behavior, not declared status, for regime classification; expands the sample including base currencies other than the dollar; examines the impact of capital controls, as well as other control variables; considers the time series properties of the data carefully; and uses cointegration and other levels-relationship analysis to provide additional insights.

Recently, the political economy of macroeconomic policy choice has increasingly been guided by the simple prescriptions of the classic trilemma. For example, policymakers often speak of the hollowing out of exchange rate regimes in a world of unstoppable capital mobility; and policy autonomy and a fixed nominal anchor present an unpleasant dichotomy for emerging markets beset by the fear of floating. Yet the trilemma is not an uncontroversial maxim, and its empirical foundations deserve greater attention. Some authors (e.g., Calvo and Reinhart 2001, 2002) have argued that under the modern float there could be limited policy autonomy given the rapid international transmission of interest rate shocks; others (e.g., Bordo and Flandreau 2003) that even under the classical gold standard there actually was considerable policy autonomy given the gold point spread and the use of gold devices and other tricks. Such arguments turn the trilemma on its head. Resolving this debate is ultimately an empirical matter, where the broadest span of data should be scrutinized. Using new techniques to study the coherence of international interest

COWLES FOUNDATION DISCUSSION PAPER NO. 1251

This chapter is concerned with methodological issues related to estimation, testing and computation in the context of structural changes in the linear models. A central theme of the review is the interplay between structural change and unit root and on methods to distinguish between the two. The topics covered are: methods related to estimation and inference about break dates for single equations with or without restrictions, with extensions to multi-equations systems where allowance is also made for changes in the variability of the shocks; tests for structural changes including tests for a single or multiple changes and tests valid with unit root or trending regressors, and tests for changes in the trend function of a series that can be integrated or trendstationary; testing for a unit root versus trend-stationarity in the presence of structural changes in the trend function; testing for cointegration in the presence of structural changes; and issues related to long memory and level shifts. Our focus is on the conceptual issues about the frameworks adopted and the assumptions imposed as they relate to potential applicability. We also highlight the potential problems that can occur with methods that are commonly used and recent work that has been done to overcome them.

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This paper considers the problem of conducting inference on the regression coefficient in a bivariate regression model with a highly persistent regressor. Gaussian power envelopes are obtained for a class of testing procedures satisfying a conditionality restriction. In addition, the paper proposes feasible testing procedures that attain these Gaussian power envelopes whether or not the innovations of the regression model are normally distributed.

AccordingtoRogoff (1995), Purchasing Power Parity (PPP) fits well one empirical feature of the data, namely the high short-run volatility of real exchange rates, but also implies that shocks should die away in one to two years (the time interval compatible with price and wage stickiness). However, existing point estimates of half-life deviationsfromPPPareintheorderof3to5years. This paper assesses how much uncertainty there is around these point estimates by using local to unity asymptotic theory to construct confidence intervals that are robust to high persistence in the presence of small sample sizes. The empirical evidence suggests that the lower bound of the confidenceintervalisaround4to8quartersformostcurrencies,whichisnotinconsistentwith PPP. However, the upper bounds are infinity for all currencies so we cannot provide conclusive evidence in favor of PPP either.