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.     

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.     

The Relative Price of Non‐traded Goods under Imperfect Competition*

We consider the role of imperfect competition in explaining the relative price of non‐traded to traded goods within the Balassa–Samuelson framework. Under imperfect competition in these two sectors, relative prices depend on both productivity and mark‐up differentials. We test this hypothesis using a panel of sectors for 12 OECD countries. The empirical evidence suggests that relative price movements are well explained by productivity and mark‐up differentials.     

Understanding Italian Inequality Trends*

This article develops a unifying framework for analysing the effects of: (i) the changing distribution of individual incomes by main factor sources, (ii) the increasing participation of wives in the labour force, and (iii) the changing distribution of family types on the distinctive trends towards inequality in equivalent household income in Italy between 1977 and 2004. Changes in the distribution of work and pension incomes explain most of the trend. The higher average likelihood of wage‐earning wives had an unequalizing effect on households on the left tail of the income distribution. Little is explained by the changing distribution of family types.     

Estimating Nonlinear Models with Multiple Fixed Effects: A Computational Note*

In this paper we consider estimation of nonlinear panel data models that include multiple individual fixed effects. Estimation of these models is complicated both by the difficulty of estimating models with possibly thousands of coefficients and also by the incidental parameters problem; that is, noisy estimates of the fixed effects when the time dimension is short contaminate the estimates of the common parameters due to the nonlinearity of the problem. We propose a simple variation of existing bias‐corrected estimators, which can exploit the additivity of the effects for numerical optimization. We exhibit the performance of the estimators in simulations.     

Inter‐industry Wage Differences and Individual Heterogeneity*

Two well‐established findings are apparent in the analyses of individual wage determination: cross‐section wage equations can account for less than half of the variance in earnings and there are large and persistent inter‐industry wage differentials. We explore these two empirical regularities using longitudinal data from the British Household Panel Survey (BHPS). We show that around 90% of the variation in earnings can be explained by observed and unobserved individual characteristics. However, small – but statistically significant – industry wage premia do remain, and there is also a role for a rich set of job and workplace controls.     

Variance Estimation for Generalized Entropy and Atkinson Inequality Indices: the Complex Survey Data Case*

We derive the sampling variances of generalized entropy and Atkinson indices when estimated from complex survey data, and show how they can be calculated straightforwardly using widely available software. We also show that, when the same approach is used to derive variance formulae for the independent and identically distributed case, it leads to estimators that are simpler than those proposed before. Both cases are illustrated with a comparison of income inequality in Britain and Germany.     

A Recursive Thick Frontier Approach to Estimating Production Efficiency*

We introduce a new panel data estimation technique for production and cost functions, the recursive thick frontier approach (RTFA). RTFA has two advantages over existing econometric frontier methods. First, technical inefficiency is allowed to be dependent on the explanatory variables of the frontier model. Secondly, RTFA does not hinge on distributional assumptions on the inefficiency component of the error term. We show by means of simulation experiments that RTFA outperforms the popular stochastic frontier approach and the ‘within’ ordinary least squares estimator for realistic parameterizations of a productivity model. Although RTFAs formal statistical properties are unknown, we argue, based on these simulation experiments, that RTFA is a useful complement to existing methods.     

The Distributional Effects of Tax‐benefit Policies under New Labour: A Decomposition Approach*

I revisit the distributional effects of tax‐benefit policy reforms under New Labour using counterfactual microsimulations embedded in a Shapley decomposition of time change in inequality and poverty indices. This makes it possible to quantify the relative effect of policy changes compared to all other changes, and to check the sensitivity of this policy effect to the use of (i) income vs. price indexation, and (ii) base vs. end period data. Inequality and poverty depth would have increased, and the sharp fall in child poverty would not have occurred, had the reforms of income support and tax credits not been implemented.     

Simulating the Reform of Means‐tested Benefits with Endogenous Take‐up and Claim Costs*

Microsimulation models are commonly used to examine the distributional impact of reforms of the means‐tested benefit system. Take‐up behaviour is related to the level of entitlement, so reform may induce changes in take‐up. We develop a stochastic simulation method and apply it to a probit model of ‘income support’ take‐up by the UK pensioners. The method allows us to adjust net income for the welfare losses because of tangible or intangible claim costs. Endogenous take‐up and claim costs both have an important impact on the simulated outcomes of the policy reform.     

Investment and Uncertainty: A Theory‐based Empirical Approach*

This paper provides empirical evidence on the dynamic effects of uncertainty on firm‐level capital accumulation. A novelty in this paper is that the firm‐level uncertainty indicator is motivated and derived from a theoretical model, the neoclassical investment model with time to build. This model also serves as the base for the empirical work, where an error‐correction approach is employed. I find a negative effect of uncertainty on capital accumulation, both in the short run and the long run. This outcome cannot be explained by the model alone. Instead, the results suggest that the predominant mechanism at work stems from irreversibility constraints.     

The Impact of Training on Productivity and Wages: Evidence from British Panel Data*

It is standard in the literature on training to use wages as a sufficient statistic for productivity. This paper examines the effects of work‐related training on direct measures of productivity. Using a new panel of British industries 1983–96 and a variety of estimation techniques we find that work‐related training is associated with significantly higher productivity. A 1% point increase in training is associated with an increase in value added per hour of about 0.6% and an increase in hourly wages of about 0.3%. We also show evidence using individual‐level data sets that is suggestive of training externalities.     

Occupational Labour Demand and the Sources of Non‐neutral Technical Change*

This article introduces a two‐step empirical approach for examining both the nature and sources of non‐neutral technical change across multiple occupations. First, conventional labour‐demand parameter estimates and unbiased tests for neutrality are obtained in the context of a flexible cost system. The resulting input‐specific indices of technical change, unconstrained with respect to time path, facilitate subsequent evaluation of proposed sources. In our application to employment decisions of airline firms, we find labour‐saving technical change that is non‐neutral across occupations. We also document occupation‐specific responses to aircraft technology adoption, route system developments and an unprecedented range of technical change elements.

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Quadratic Engel Curves with Measurement Error: Evidence from a Budget Survey*

This paper examines the importance of accounting for measurement error in total expenditure in the estimation of Engel curves, based on the 1994 Ethiopian Urban Household Survey. Using Lewbel's [Review of Economics and Statistics (1996 ), Vol. 78, pp. 718–725] estimator for demand models with correlated measurement errors in the dependent and independent variables, we find robust evidence of a quadratic relationship between food share and total expenditure in the capital city, and significant biases in various estimators that do not correct for correlated measurement errors.     

Edgeworth expansions and normalizing transforms for inequality measures

Finite sample distributions of studentized inequality measures differ substantially from their asymptotic normal distribution in terms of location and skewness. We study these aspects formally by deriving the second-order expansion of the first and third cumulant of the studentized inequality measure. We state distribution-free expressions for the bias and skewness coefficients. In the second part we improve over first-order theory by deriving Edgeworth expansions and normalizing transforms. These normalizing transforms are designed to eliminate the second-order term in the distributional expansion of the studentized transform and converge to the Gaussian limit at rate O(n⁻¹)$O\left(n^{-1}\right)$. This leads to improved confidence intervals and applying a subsequent bootstrap leads to a further improvement to order O(n^−3/2)$O\left(n^{-3/2}\right)$. We illustrate our procedure with an application to regional inequality measurement in Côte d’Ivoire.     

Turning Unemployment into Self‐Employment: Effectiveness of Two Start‐Up Programmes*

Turning unemployment into self‐employment has become a major focus of German active labour market policy (ALMP) in recent years. If effective, this would not only reduce Germany's persistently high unemployment rate, but also increase its notoriously low self‐employment rate. Empirical evidence on the effectiveness of such programmes is scarce. We evaluate the effectiveness of two start‐up programmes for the unemployed, where we include the probability of being employed, the probability of being unemployed and personal income as outcome variables. Our results show that at the end of the observation period, both programmes are effective. The considerable positive effects present a stark contrast to findings from evaluations of other German ALMP programmes in recent years. Hence, ALMP programmes aimed at moving the unemployed into self‐employment may prove to be among the most effective, both in Germany and elsewhere.     

A Simple Panel‐CADF Test for Unit Roots*

In this paper, we propose a simple extension to the panel case of the covariate‐augmented Dickey–Fuller (CADF) test for unit roots developed in Hansen (1995) . The panel test we propose is based on a P values combination approach that takes into account cross‐section dependence. We show that the test has good size properties and gives power gains with respect to other popular panel approaches. An empirical application is carried out for illustration purposes on international data to test the purchasing power parity (PPP) hypothesis.     

Merger Cycles: A Frequency Domain Approach*

Using frequency domain techniques, a cycle of 6‐year duration at the aggregate level and coherent sectoral cycles of average 5‐year duration are found in UK merger activity between 1969 and 2005. It is shown that business and capital market cycles jointly are causal for the merger cycle but the capital market cycle alone is not, suggesting that merger cycles may reflect disequilibria and/or market mis‐valuation. Although the possibility of disequilibrium or strong behavioural influences will complicate social evaluation, no reason is found to advise against the current UK policy stance upon mergers.     

GMM Estimation with Non‐causal Instruments*

This note provides a warning against careless use of the generalized method of moments (GMM) with time series data. We show that if time series follow non‐causal autoregressive processes, their lags are not valid instruments, and the GMM estimator is inconsistent. Moreover, endogeneity of the instruments may not be revealed by the J‐test of overidentifying restrictions that may be inconsistent and has, in general, low finite‐sample power. Our explicit results pertain to a simple linear regression, but they can easily be generalized. Our empirical results indicate that non‐causality is quite common among economic variables, making these problems highly relevant.     

Revisiting Error‐Autocorrelation Correction: Common Factor Restrictions and Granger Non‐Causality*

The paper questions the appropriateness of the practice known as ‘error‐autocorrelation correcting’ in linear regression, by showing that adopting an AR(1) error formulation is equivalent to assuming that the regressand does not Granger cause any of the regressors. This result is used to construct a new test for the common factor restrictions, as well as investigate – using Monte Carlo simulations – other potential sources of unreliability of inference resulting from this practice. The main conclusion is that when the Granger cause restriction is false, the ordinary least square and generalized least square estimators are biased and inconsistent, and using autocorrelation‐consistent standard errors does not improve the reliability of inference.