TESTING FOR STATIONARITY IN HETEROGENEOUS PANEL DATA IN THE CASE OF MODEL MISSPECIFICATION

This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N →∞ simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro‐panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over‐rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (≤10).     

PREDICTING CURRENCY CRISES WITH A NESTED LOGIT MODEL

Abstract.  This paper is the first to apply a nested logit model to measure the probabilities of speculative attacks and the probabilities of successful defences by the central banks. This model allows us to predict the probability not only of speculative attacks but also of successful defences, given attacks. It also provides a framework for analysing the degree to which different factors affect the likelihood of attacks and defences. We find strong evidence that external illiquidity and financial fragility are reliable predictors of currency crises. The results shed light on the validity of the three generations of currency crisis models.     

TESTING THE ONE‐WAY EFFECT IN THE PRESENCE OF TREND BREAKS*

This paper provides an approach to testing the measures of the one‐way effect for cointegrated vector time‐series in the presence of trend breaks. We propose Wald testing the measures and their computational algorithm, an extension of previous work by Hosoya and Yao and Hosoya, to the case where trend breaks are explicitly taken into account in the cointegration relationship. On the basis of the proposed inferential method and the derived evidence, we present a causal structure characterization of money supply and income as well as interest rates for the last 44 years of the Japanese economy, and contrast it with the results of Yao and Hosoya.     

TESTING FOR STATIONARITY WITH A BREAK IN PANELS WHERE THE TIME DIMENSION IS FINITE

In this paper, we consider the case of finite time dimension in the panel stationarity tests with structural breaks. By fixing T, the finite sample properties of the tests for both micro (T small and N large) and macro (both T and N large) panel data are generally greatly improved. More importantly, the derivation of the tests for finite T and , as opposed to joint asymptotic where N and simultaneously, avoids the imposition of the rate condition making the test valid for any (T, N) blend. Four models corresponding to the usual combination of breaks are considered. The asymptotic distributions of the test are derived under the null hypothesis and are shown to be normally distributed. Their moments for T fixed are derived analytically employing Ghazal’s corollary 1. The case with unknown breaks is also considered. The proposed tests have generally empirical sizes that are very close to the nominal size. The Monte Carlo simulations show that the power of the test statistics increases substantially with N and T.     

USING A LAPLACE APPROXIMATION TO ESTIMATE THE RANDOM COEFFICIENTS LOGIT MODEL BY NONLINEAR LEAST SQUARES*

Current methods of estimating the random coefficients logit model employ simulations of the distribution of the taste parameters through pseudo‐random sequences. These methods suffer from difficulties in estimating correlations between parameters and computational limitations such as the curse of dimensionality. This article provides a solution to these problems by approximating the integral expression of the expected choice probability using a multivariate extension of the Laplace approximation. Simulation results reveal that our method performs very well, in terms of both accuracy and computational time.     

THE EFFECTIVENESS OF NON‐TRADITIONAL MONETARY POLICY MEASURES: THE CASE OF THE BANK OF JAPAN*

This paper summarizes non‐traditional monetary policy measures adopted by the Bank of Japan (BOJ) during the last 2 decades and by other G7 central banks since the start of the current global financial turmoil and analyses the effectiveness of such measures. The paper begins with a typology of policies usable near the zero lower bound on interest rates. They are: (i) forward guidance of future policy rates; (ii) targeted asset purchases; and (iii) quantitative easing. Using this typology, I review the measures adopted by the BOJ and other central banks. I then offer a news analysis of the effects of the measures adopted by the BOJ on asset prices, comparing them with those adopted by the Fed. Many of the measures, with the exception of strategy (iii), are shown to have moved asset prices in the expected directions. Another exception is that most of the monetary easing measures failed to weaken the yen. Despite some effects on asset prices, however, the measures have failed to stop the deflationary trend of the Japanese economy clearly. I discuss some possible reasons for this and more general implications for monetary policy.     

THE INF‐T TEST FOR A UNIT ROOT AGAINST ASYMMETRIC EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE MODELS

This paper proposes a new test for a unit root against an alternative of asymmetric exponential smooth transition autoregressive models, by extending the infimum test developed by Park and Shintani. Simulation results suggest that the test performs reasonably well in finite samples. The proposed test is also applied to real exchange rates to examine their asymmetric and nonlinear mean‐reverting properties.     

Testing for joint significance in nonstationary binary choice model

This paper investigates the test of joint significance for binary choice model with multiple integrated explanatory variables. It is found that for the widely used logit and probit models, even though the estimators have a different convergence rate under null hypothesis compared with the case under alternative, the commonly used Wald statistic is still useful, and asymptotically chi-squared.     

Inverse demand systems and choice of functional form

Barten (Empirical Economics 18 (1993) 129) recently advocated estimation of a synthetic demand system that mechanically nests four other popular differential demand models. This paper follows a similar strategy, but in the context of four inverse share-equation demand systems: The Inverse Translog Demand System (ITLDS); the Inverse Almost Ideal Demand System (IAIDS); the Inverse Lewbel Demand System (ILDS); and the Inverse Non-Separable Linear Expenditure System (INLES). Each of these specifications is artificially nested in a Hybrid Inverse Demand System (HIDS). An empirical application to three categories of quarterly U.S. meat demand data over the period 1961-1996 indicates the HIDS is a preferred specification.     

THE WELFARE PERFORMANCE OF SEQUENTIAL PRICING MECHANISMS*

Consumers are commonly required to subscribe to particular tariff options before uncertainty regarding their future purchases gets resolved. Since the general comparison of welfare performance of different pricing mechanisms is ambiguous, this article empirically evaluates the expected welfare associated with standard nonlinear pricing and optional tariffs by using information directly linked to the type of individual consumers. Results show that tariffs composed of nonlinear options do not necessarily outperform simpler pricing strategies in terms of expected profits. Furthermore, evidence suggests that a menu of optional two‐part tariffs dominates any other pricing strategy from an expected welfare perspective.     

Benford's Law as an Indicator of Fraud in Economics

Abstract. Contrary to intuition, first digits of randomly selected data are not uniformly distributed but follow a logarithmically declining pattern, known as Benford's law. This law is increasingly used as a 'doping check' for detecting fraudulent data in business and administration. Benford's law also applies to regression coefficients and standard errors in empirical economics. This article reviews Benford's law and examines its potential as an indicator of fraud in economic research. Evidence from a sample of recently published articles shows that a surprisingly large proportion of first digits, but not of second digits, contradicts Benford's law.     

THE EFFECTS OF THE BANK OF JAPAN'S ZERO INTEREST RATE COMMITMENT AND QUANTITATIVE MONETARY EASING ON THE YIELD CURVE: A MACRO‐FINANCE APPROACH*

This paper empirically investigates the effects of the Bank of Japan's (BOJ) zero interest rate commitment and quantitative monetary easing on the yield curve. Applying a macro‐finance approach, we decompose interest rates into expectations and risk premium components and extract the market's perception of the BOJ's policy stance. We make clear the counterfactual policy without the BOJ's commitment. We find some evidence that the commitment lowered interest rates and mat raising the reserve target may have been perceived as a signal indicating the BOJ's accommodative policy stance. The portfolio rebalancing effect has not been found to be significant.     

Bootstrap Methods in Econometrics*

There are many bootstrap methods that can be used for econometric analysis. In certain circumstances, such as regression models with independent and identically distributed error terms, appropriately chosen bootstrap methods generally work very well. However, there are many other cases, such as regression models with dependent errors, in which bootstrap methods do not always work well. This paper discusses a large number of bootstrap methods that can be useful in econometrics. Applications to hypothesis testing are emphasized, and simulation results are presented for a few illustrative cases.     

Weak exogeneity in partially nonstationary models

This paper is dedicated to analysing the conditions for weak exogeneity in partially nonstationary models. After adopting a particular identification regime which is based on a triangularization of the parameters of the cointegration relations, we show that the conditions for weak exogeneity developed in the literature can be stated in terms of the parameters of the so-called structural form. This alternative presentation of the conditions permits new interpretations and provides fresh insights on how to test the exogeneity hypothesis.     

QUANTILE FORECASTS OF FINANCIAL RETURNS USING REALIZED GARCH MODELS*

This article applies the realized generalized autoregressive conditional heteroskedasticity (GARCH) model, which incorporates the GARCH model with realized volatility, to quantile forecasts of financial returns, such as Value‐at‐Risk and expected shortfall. Student's t‐ and skewed Student's t‐distributions as well as normal distribution are used for the return distribution. The main results for the S&P 500 stock index are: (i) the realized GARCH model with the skewed Student's t‐distribution performs better than that with the normal and Student's t‐distributions and the exponential GARCH model using the daily returns only; and (ii) using the realized kernel to take account of microstructure noise does not improve the performance.     

Threshold effects in panel data stochastic frontier models of dairy production in Canada

One of the most enduring problems in econometrics is how to properly account for heterogeneity among firms. Threshold regression models are intuitively appealing methods to deal with this issue. We consider a fixed-effect panel data stochastic frontier model (Schmidt and Sickles, 1984; Martin-Marcos and Suarez-Galvez, 2000) and, relying on Hansen (1999, 2000a), we propose an estimator that accommodates multiple thresholds. Our model assumes absence of any unmeasured time invariant heterogeneity across firms as in Greene (2005, p. 277). Slope and threshold parameters can be estimated using a within estimator combined with a grid search over the threshold parameters. Testing for threshold effects is problematic because threshold parameters are not identified under the null hypothesis, a case of the so-called Davies' problem. We apply the bootstrap procedure proposed by Hansen (1999, 2000a) to test for the presence of thresholds. An asymptotic confidence set for the threshold parameter can be obtained by inverting an LR test, using the distribution result presented in Hansen (1999, 2000a). Our empirical application features a panel of Quebec dairy farms. We use farm size as the threshold variable. The presence of a trend in the specification matters for the determination of the number of thresholds. Technical efficiency scores and rankings of farms estimated from competing model specifications are highly correlated and do not vary significantly across groups of farm sizes defined by the threshold parameter values.     

Unit Root Investigation of Greek Real Money Supply and GDP

In this article, the time series of Greek real GDP and real money supply are investigated for the presence of a unit root, allowing for maximum two breaks which take place at an unknown point in time. This methodology is preferred to conventional Dickey & Fuller tests because the covered time horizon, namely from 1858 to 1938, is characterized by a number of very important events, the nature of which is either economic or historical. In addition, time series stationarity is checked through a Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) test.University of Macedonia—Greece. The article was presented at the Fifty-Ninth International Atlantic Economic Conference, London, England, March 9–13, 2005     

A cautionary note on tests of overidentifying restrictions

In this note, we argue that tests of overidentifying restrictions give little information on the validity of the moment conditions implied by the underlying economic model, and therefore are mute about the possibility of identifying the parameters of interest.     

基于Logit模型的奶农收入影响因素分析

散户奶农利润降低导致奶农增收困难成为近年来奶业发展的一大问题。本文在对内蒙古呼和浩特市101户奶农调查的基础上,建立Logit模型分析影响奶农收入的因素,结果表明家庭劳动力人数、养殖规模、养殖时间、饲料地面积、饲料成本均对奶农收入有显著性的影响,为此政府在稳定饲料价格的同时,要鼓励奶农提高劳动生产率,合理确定养殖规模等。