Testing Uncovered Interest Rate Parity and Term Structure Using a Three‐regime Threshold Unit Root VECM: An Application to the Swiss ‘Isle’ of Interest Rates*

In this article, a three‐regime multivariate threshold vector error correction model with a ‘band of inaction’ is formulated to examine uncovered interest rate parity (UIRP) and expectation hypothesis of the term structure (EHTS) of interest rates for Switzerland. Combining both UIRP and EHTS in a model that allows for nonlinearities, we investigate whether the Swiss advantage is disappearing with respect to Europe. Our results favour threshold cointegration and show that both hypotheses hold, at least in one of the three regimes of the process for Switzerland/Germany. The same is not true between Switzerland and the United States.     

Exchange Rate Pass‐through to Trade Prices: The Role of Nonlinearities and Asymmetries*

A standard assumption in the empirical literature is that exchange rate pass‐through is both linear and symmetric. This study tests these assumptions for export and import prices in the G7 economies. It focuses on non‐linearities in the reaction of profit margins to exchange rate movements, which may arise from the presence of price rigidities and switching costs. Nonlinearities are characterized by augmenting a standard linear model with polynomial functions of the exchange rate and with interactive dummy variables. The results suggest that nonlinearities and especially asymmetries cannot be ignored, although their magnitude varies noticeably across countries.     

The Hazard Rate of Foreign Direct Investment: A Structural Estimation of a Real‐option Model*

The hazard rate of investment is derived within a real‐option model, and its properties are analysed so as to directly study the relation between uncertainty and investment. Maximum likelihood estimates of the hazard are calculated using a sample of multinational enterprises (MNEs) that invested in Central and Eastern Europe over the period 1990–98. Employing a standard, non‐parametric specification of the hazard, our measure of uncertainty has a negative effect on investment, but the reduced‐form model is unable to control for nonlinearities in the relationship. The structural estimation of the option‐based hazard is instead able to account for the nonlinearities and exhibits a significant value of waiting, although the latter is independent of our measure of uncertainty. This finding supports the existence of alternative channels through which uncertainty can affect investment.     

Panel Unit‐root Tests for Cross‐sectionally Correlated Panels: A Monte Carlo Comparison*

This paper deals with the finite‐sample performance of a set of unit‐root tests for cross‐correlated panels. Most of the available macroeconomic time series cover short time periods. The lack of information, in terms of time observations, implies that univariate tests are not powerful enough to reject the null of a unit‐root while panel tests, by exploiting the large number of cross‐sectional units, have been shown to be a promising way of increasing the power of unit‐root tests. We investigate the finite sample properties of recently proposed panel unit‐root tests for cross‐sectionally correlated panels. Specifically, the size and power of Choi's [Econometric Theory and Practice: Frontiers of Analysis and Applied Research: Essays in Honor of Peter C. B. Phillips, Cambridge University Press, Cambridge (2001)], Bai and Ng's [Econometrica (2004), Vol. 72, p. 1127], Moon and Perron's [Journal of Econometrics (2004), Vol. 122, p. 81], and Phillips and Sul's [Econometrics Journal (2003), Vol. 6, p. 217] tests are analysed by a Monte Carlo simulation study. In synthesis, Moon and Perron's tests show good size and power for different values of T and N, and model specifications. Focusing on Bai and Ng's procedure, the simulation study highlights that the pooled Dickey–Fuller generalized least squares test provides higher power than the pooled augmented Dickey–Fuller test for the analysis of non‐stationary properties of the idiosyncratic components. Choi's tests are strongly oversized when the common factor influences the cross‐sectional units heterogeneously.     

Explaining Firms’ Export Behaviour: R&D,Spillovers and the Destination Market*

We examine the importance of a firm's own R&D activity and intra‐sectoral spillovers on the decision to export and the export intensity using firm level panel data for Spain for the period 1990–98. Own R&D activity is found to be an important determinant of export activity. There is little evidence to suggest that Spanish firms benefit from spillovers of the exporting activity of others. However, there is evidence that R&D spillovers exert positive effects on firms’ export ratios. We find a larger marginal impact of R&D spillovers on export intensity of firms exporting to other OECD countries than those exporting to non‐OECD nations.     

Fiscal policy and asset markets: A semiparametric analysis

Using a flexible semiparametric varying coefficient model specification, this paper examines the role of fiscal policy on the US asset markets (stocks, corporate and treasury bonds). We consider two possible roles of fiscal deficits (or surpluses): as a separate direct information variable and as a (indirect) conditioning information variable indicating binding constraints on monetary policy actions. The results show that the impact of monetary policy on the stock market varies, depending on fiscal expansion or contraction. The impact of fiscal policy on corporate and treasury bond yields follow similar patterns as in the equity market. The results are consistent with the notion of strong interdependence between monetary and fiscal policies.     

Money‐output Causality Revisited – A Bayesian Logistic Smooth Transition VECM Perspective*

This article proposes a Bayesian approach to examining money‐output causality within the context of a logistic smooth transition vector error correction model. Our empirical results provide substantial evidence that the postwar US money‐output relationship is nonlinear, with regime changes mainly governed by the output growth and price levels. Furthermore, we obtain strong support for nonlinear Granger causality from money to output, although there is also some evidence for models indicating that money is not Granger causal or long‐run causal to output.     

The Yen Real Exchange Rate may be Stationary after all: Evidence from Non‐linear Unit‐root Tests*

The empirical literature that tests for purchasing power parity (PPP) by focusing on the stationarity of real exchange rates has so far provided, at best, mixed results. The behaviour of the yen real exchange rate has most stubbornly challenged the PPP hypothesis and deepened this puzzle. This paper contributes to this discussion by providing new evidence on the stationarity of bilateral yen real exchange rates. We employ a non‐linear version of the augmented Dickey–Fuller test, based on an exponentially smooth‐transition autoregressive model (ESTAR) that enhances the power of the tests against mean‐reverting non‐linear alternative hypotheses. Our results suggest that the bilateral yen real exchange rates against the other G7 and Asian currencies were mean reverting during the post‐Bretton Woods era. Thus, the real yen behaviour may not be so different after all but simply perceived to be so because of the use of a restrictive alternative hypothesis in previous tests.     

Estimation Bias and Inference in Overlapping Autoregressions: Implications for the Target‐Zone Literature*

Samples with overlapping observations are used for the study of uncovered interest rate parity, the predictability of long‐run stock returns and the credibility of exchange rate target zones. This paper quantifies the biases in parameter estimation and size distortions of hypothesis tests of overlapping linear and polynomial autoregressions, which have been used in target‐zone applications. We show that both estimation bias and size distortions of hypothesis tests are generally larger, if the amount of overlap is larger, the sample size is smaller, and autoregressive root of the data‐generating process is closer to unity. In particular, the estimates are biased in a way that makes it more likely that the predictions of the Bertola–Svensson model will be supported. Size distortions of various tests also turn out to be substantial even when using a heteroskedasticity and autocorrelation‐consistent covariance matrix.     

A Non‐parametric Examination of Capital–Skill Complementarity*

This paper uses non‐parametric kernel methods to construct observation‐specific elasticities of substitution for a balanced panel of 73 developed and developing countries to examine the capital–skill complementarity hypothesis. The exercise shows some support for capital–skill complementarity, but the strength of the evidence depends upon the definition of skilled labour and the elasticity of substitution measure being used. The added flexibility of the non‐parametric procedure is also capable of uncover ing that the elasticities of substitution vary across countries, groups of countries and time periods.     

A No‐Arbitrage Structural Vector Autoregressive Model of the UK Yield Curve*

This article combines a Structural Vector Autoregression with a no‐arbitrage approach to build a multifactor Affine Term Structure Model (ATSM). The resulting No‐Arbitrage Structural Vector Autoregressive (NASVAR) model implies that expected excess returns are driven by structural macroeconomic shocks. This is in contrast with a standard ATSM, in which agents are concerned with non‐structural risks. As a simple application, we study the effects of supply, demand and monetary policy shocks on the UK yield curve. We show that all structural shocks affect the slope of the yield curve, with demand and supply shocks accounting for a large part of the time variation in bond yields.     

A Semiparametric Analysis of the Term Structure of the US Interest Rates*

The short end of the US$ term structure of interest rates is analysed allowing for the possibility of fractional integration and cointegration. This approach permits mean‐reverting dynamics for the data and the existence of a common long run stochastic trend to be maintained simultaneously. We estimate the model for the period 1963–2006 and find it compatible with this structure. The restriction that the data are I(1) and the errors are I(0) is rejected, mainly because the latter still display long memory. This result is consistent with a model of monetary policy in which the Central Bank operates affecting contracts with short term maturity, and the impulses are transmitted to contracts with longer maturities and then to the final goals. However, the transmission of the impulses along the term structure cannot be modelled using the Expectations Hypothesis.     

The Impact of Short‐ and Long‐run Exchange Rate Uncertainty on Investment: A Panel Study of Industrial Countries*

We examine the relationship between aggregate investment and exchange rate uncertainty in the G7, using panel estimation and decomposition of volatility derived from the components generalized autoregressive conditionally heteroscedastic (GARCH) model. Our dynamic panel approach takes account of potential cross‐sectional heterogeneity, which can lead to bias in estimation. We find that for a poolable subsample of European countries, it is the transitory and not the permanent component of volatility which adversely affects investment. To the extent that short‐run uncertainty in the CGARCH model characterizes higher frequency shocks generated by volatile short‐term capital flows, these are most deleterious for investment.     

Trade,Technology and the Labour Market: The Case of South Africa*

This study advances previous work on the effects of trade and technological change on labour markets within the framework of Heckscher–Ohlin trade theory. We provide evidence for an unskilled labour abundant developing country by employing dynamic heterogeneous panel estimation techniques. For South African manufacturing, trade‐mandated increases in earnings are positive for labour and negative for capital whilst technology‐mandated increases are negative for both factors. We also find it important to take account of endogeneity issues in analysing the impact of technology and price changes on factor returns and in isolating factor‐ and sector‐bias of technological changes.     

Further Evidence on PPP Adjustment Speeds: the Case of Effective Real Exchange Rates and the EMS*

Two different approaches intend to resolve the ‘puzzling’ slow convergence to purchasing power parity (PPP) reported in the literature [see Rogoff (1996) , Journal of Economic Literature, Vol. 34.] On the one hand, there are models that consider a non‐linear adjustment of real exchange rate to PPP induced by transaction costs. Such costs imply the presence of a certain transaction band where adjustment is too costly to be undertaken. On the other hand, there are models that relax the ‘classical’ PPP assumption of constant equilibrium real exchange rates. A prominent theory put together by Balassa (1964, Journal of Political Economy, Vol. 72) and Samuelson (1964 Review of Economics and Statistics, Vol. 46) , the BS effect, suggests that a non‐constant real exchange rate equilibrium is induced by different productivity growth rates between countries. This paper reconciles those two approaches by considering an exponential smooth transition‐in‐deviation non‐linear adjustment mechanism towards non‐constant equilibrium real exchange rates within the EMS (European Monetary System) and effective rates. The equilibrium is proxied, in a theoretically appealing manner, using deterministic trends and the relative price of non‐tradables to proxy for BS effects. The empirical results provide further support for the hypothesis that real exchange rates are well described by symmetric, nonlinear processes. Furthermore, the half‐life of shocks in such models is found to be dramatically shorter than that obtained in linear models.     

Exact Skewness–Kurtosis Tests for Multivariate Normality and Goodness‐of‐Fit in Multivariate Regressions with Application to Asset Pricing Models*

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross‐equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared with a simulation‐based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal and stable error distributions. In the Gaussian case, finite‐sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi‐stage Monte Carlo test methods. For non‐Gaussian distribution families involving nuisance parameters, confidence sets are derived for the nuisance parameters and the error distribution. The tests are applied to an asset pricing model with observable risk‐free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over 5‐year subperiods from 1926 to 1995.     

Density Nowcasts and Model Combination: Nowcasting Euro‐Area GDP Growth over the 2008–09 Recession*

Combined density nowcasts for quarterly Euro‐area GDP growth are produced based on the real‐time performance of component models. Components are distinguished by their use of ‘hard’ and ‘soft’, aggregate and disaggregate, indicators. We consider the accuracy of the density nowcasts as within‐quarter indicator data accumulate. We find that the relative utility of ‘soft’ indicators surged during the recession. But as this instability was hard to detect in real‐time it helps, when producing density nowcasts unknowing any within‐quarter ‘hard’ data, to weight the different indicators equally. On receipt of ‘hard’ data for the second month in the quarter better calibrated densities are obtained by giving a higher weight in the combination to ‘hard’ indicators.     

Leaning into the Wind: A Structural VAR Investigation of UK Monetary Policy*

This paper adapts Uhlig's [Journal of Monetary Economics (2005) forthcoming] sign restriction identification methodology to investigate the effects of UK monetary policy using a structural vector autoregression (VAR). It shows that shocks which can reasonably be described as monetary policy shocks have played only a small role in the total variation of UK monetary and macroeconomic variables. Most of the variation in UK monetary variables has been due to their systematic reaction to other macroeconomic shocks, namely non‐monetary aggregate demand, aggregate supply, and oil price shocks. We also find, without imposing any long run identifying restrictions, that aggregate supply shocks have permanent effects on output.     

The Long‐Run Impact of Foreign Aid in 36 African Countries: Insights from Multivariate Time Series Analysis*

We comprehensively analyse the long‐run effect of foreign aid (ODA) on key macroeconomic variables in 36 sub‐Saharan African countries from the mid‐1960s to 2007, using a well‐specified cointegrated VAR model as statistical benchmark. Results provide broad support for a positive long‐run impact of ODA flows on the macroeconomy. In contrast, we find little evidence supporting the thesis that aid has been harmful. From a methodological point of view we highlight the importance of transparency in reporting results, especially when the hypothesis being tested differs from theoretical expectations, and we identify reasons for econometrically inadequate results in the literature.     

On the Choice of Control Variables in the Crime Equation*

Although control variables are the reason for multiple regression, surprising little attention is given to the process of locating and selecting the controls. If important controls are omitted, estimates can be biased and inconsistent whereas using too many controls can reduce efficiency and mask effects. We advocate a much broader search for controls than is customary, at least in the crime literature, and then the use of the general‐to‐specific methodology to select the relevant controls. We illustrate this procedure using a fixed effects panel data design evaluating the effect of legalized abortion on crime.