We consider the problem of estimating and testing for multiple breaks in a single-equation framework with regressors that are endogenous, i.e. correlated with the errors. We show that even in the presence of endogenous regressors it is still preferable, in most cases, to simply estimate the break dates and test for structural change using the usual ordinary least squares (OLS) framework. Except for some knife-edge cases, it delivers estimates of the break dates with higher precision and tests with higher power compared to those obtained using an instrumental variable (IV) method. Also, the OLS method avoids potential weak identification problems caused by weak instruments. To illustrate the relevance of our theoretical results, we consider the stability of the New Keynesian hybrid Phillips curve. IV-based methods only provide weak evidence of instability. On the other hand, OLS-based ones strongly indicate a change in 1991:Q1 and that after this date the model loses all explanatory power. Copyright © 2013 John Wiley & Sons, Ltd.

This paper considers estimation of censored panel-data models with individual-specific slope heterogeneity. The slope heterogeneity may be random (random slopes model) or related to covariates (correlated random slopes model). Maximum likelihood and censored least-absolute deviations estimators are proposed for both models. The estimators are simple to implement and, in the case of maximum likelihood, lead to straightforward estimation of partial effects. The rescaled bootstrap suggested by Andrews (Econometrica 2000; 68: 399–405) is used to deal with the possibility of variance parameters being equal to zero. The methodology is applied to an empirical study of Dutch household portfolio choice, where the outcome variable (portfolio share in safe assets) has corner solutions at zero and one. As predicted by economic theory, there is strong evidence of correlated random slopes for the age profiles, indicating a heterogeneous age profile of portfolio adjustment that varies significantly with other household characteristics. Copyright © 2013 John Wiley & Sons, Ltd.

The effect of a program or treatment may vary according to observed characteristics. In such a setting, it may not only be of interest to determine whether the program or treatment has an effect on some sub-population defined by these observed characteristics, but also to determine for which sub-populations, if any, there is an effect. This paper treats this problem as a multiple testing problem in which each null hypothesis in the family of null hypotheses specifies whether the program has an effect on the outcome of interest for a particular sub-population. We develop our methodology in the context of PROGRESA, a large-scale poverty-reduction program in Mexico. In our application, the outcome of interest is the school enrollment rate and the sub-populations are defined by gender and highest grade completed. Under weak assumptions, the testing procedure we construct controls the familywise error rate—the probability of even one false rejection—in finite samples. Similar to earlier studies, we find that the program has a significant effect on the school enrollment rate, but only for a much smaller number of sub-populations when compared to results that do not adjust for multiple testing. Copyright © 2013 John Wiley & Sons, Ltd.

Reliable estimates of crime detection probabilities could help in designing better sanctions and improve our understanding of the efficiency of law enforcement. For cartels, we only have limited knowledge on the rate at which these illegal practices are discovered. In comparison to previous works, this paper offers a more parsimonious and simple-to-use method to estimate time-dependent cartel discovery rates, while allowing for heterogeneity across firms. It draws on capture–recapture methods that are frequently used in ecology to make inferences on various wildlife population characteristics. An application of this method provides evidence that less than a fifth of cartelising firms are discovered. Copyright © 2013 John Wiley & Sons, Ltd.

Empirical modelling of the linkages between the euro area and the USA requires an open economy framework. The methodology proposed in this paper achieves identification of a structural vector error correction model by supplementing restrictions from economic theory with assumptions for the direction of causality in cross-country contemporaneous relationships. Our baseline model assumes contemporaneous causality runs from the USA to the euro area for both output and inflation, with monetary policy domestically focused. The role of the USA as leading the euro area business cycle is reinforced by our results, but strong bidirectional cross-country interactions are uncovered for inflation and interest rates. Copyright © 2013 John Wiley & Sons, Ltd.

This paper studies the role of the Federal Reserve's policy in the recent boom and bust of the housing market, and in the ensuing recession. By estimating a structural dynamic factor model on a panel of 109 US quarterly variables from 1982 to 2010, we find that, although the Federal Reserve's policy between 2002 and 2004 was slightly expansionary, its contribution to the recent housing cycle was negligible. We also show that a more restrictive policy would have smoothed the cycle but not prevented the recession. We thus find no role for the Federal Reserve in causing the recession. Copyright © 2013 John Wiley & Sons, Ltd.

We develop a panel data model explaining answers to subjective probabilities about binary events and estimate it using data from the Health and Retirement Study on six such probabilities. The model explicitly accounts for several forms of ‘reporting behavior’: rounding, focal point ‘50%’ answers and item nonresponse. We find observed and unobserved heterogeneity in the tendencies to report rounded values or a focal answer, explaining persistency in 50% answers over time. Focal 50% answers matter for some of the probabilities. Incorporating reporting behavior does not have a large effect on the estimated distribution of the genuine subjective probabilities. Copyright © 2013 John Wiley & Sons, Ltd.

We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short-run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper we discuss how the point and density forecasting performance of Bayesian vector autoregressions (BVARs) is affected by a number of specification choices. We adopt as a benchmark a common specification in the literature, a BVAR with variables entering in levels and a prior modeled along the lines of Sims and Zha (International Economic Review 1998; 39: 949–968). We then consider optimal choice of the tightness, of the lag length and of both; evaluate the relative merits of modeling in levels or growth rates; compare alternative approaches to h-step-ahead forecasting (direct, iterated and pseudo-iterated); discuss the treatment of the error variance and of cross-variable shrinkage; and assess rolling versus recursive estimation. Finally, we analyze the robustness of the results to the VAR size and composition (using also data for France, Canada and the UK, while the main analysis is for the USA). We obtain a large set of empirical results, but the overall message is that we find very small losses (and sometimes even gains) from the adoption of specification choices that make BVAR modeling quick and easy, in particular for point forecasting. This finding could therefore further enhance the diffusion of the BVAR as an econometric tool for a vast range of applications. Copyright © 2013 John Wiley & Sons, Ltd.

This article evaluates an expansion of employer-mandated sick leave from 80% to 100% of forgone gross wages in Germany. We employ and compare parametric difference-in-difference (DID), matching DID and mixed approaches. Overall workplace absences increased by at least 10% or 1 day per worker per year. We show that taking partial compliance into account increases coefficient estimates. Further, heterogeneity in response behavior was of great importance. There is no evidence that the increase in sick leave improved employee health, a finding that supports a shirking explanation. Finally, we provide evidence on potential labor market adjustments to the reform. Copyright © 2013 John Wiley & Sons, Ltd.

This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (Econometrica 1989; 57: 307–333). Two models are overlapping when the true model contains just a subset of variables common to the larger sets of variables included in the competing forecasting models. We consider an out-of-sample version of the two-step testing procedure recommended by Vuong but also show that an exact one-step procedure is sometimes applicable. When the models are overlapping, we provide a simple-to-use fixed-regressor wild bootstrap that can be used to conduct valid inference. Monte Carlo simulations generally support the theoretical results: the two-step procedure is conservative, while the one-step procedure can be accurately sized when appropriate. We conclude with an empirical application comparing the predictive content of credit spreads to growth in real stock prices for forecasting US real gross domestic product growth. Copyright © 2013 John Wiley & Sons, Ltd.

We study the effects of financial incentives on retirement decisions using stated preference data. Dutch survey respondents were given hypothetical retirement scenarios describing age(s) of (partial and full) retirement and replacement rate(s). A stylized model is estimated in which utility is the discounted sum of within-period utilities that depend on employment status and income. Parameters of the utility function vary with observed and unobserved characteristics. Simulations show that the income and substitution effects of pensions as a function of the retirement age are substantial and larger than according to studies using data on actual retirement decisions in the Netherlands. Copyright © 2013 John Wiley & Sons, Ltd.

Although speculative activity is central to black markets for currency, the out-of-sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out-of-sample performance of linear models and non-parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals-based models outperform the benchmark in out-of-sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real-time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper we investigate the demand for gasoline in Canada using recent annual expenditure data from the Canadian Survey of Household Spending, over a 13-year period from 1997 to 2009, on three expenditure categories in the transportation sector: gasoline, local transportation, and intercity transportation. In doing so, we use three of the most widely used locally flexible functional forms, the Almost Ideal Demand System (AIDS) of Deaton and Muellbauer (1980), the quadratic AIDS (QUAIDS) of Banks et al. (1997)—an extension of the simple AIDS model that can generate quadratic Engel curves—and the Minflex Laurent model of Barnett (1983), which can also generate quadratic Engel curves. We pay explicit attention to economic regularity, argue that unless regularity is attained by luck, flexible functional forms should always be estimated subject to regularity as suggested by Barnett (2002), and impose local curvature to produce inference consistent with neoclassical microeconomic theory. Our findings indicate that the curvature-constrained Minflex Laurent model is the only model that is able to provide theoretically consistent estimates of the Canadian demand for gasoline. Our estimates show that the own-price elasticity for gasoline demand in Canada is between − 0.738 and − 0.570 —less elastic than previously reported in the literature. Copyright © 2013 John Wiley & Sons, Ltd.

One of the major challenges of empirical tax research is the identification and calculation of appropriate tax data. While there is consensus that average marginal tax rates are most suitable for studying the effects of tax policy on economic growth, because of data limitations the calculation of marginal tax rates has been limited to the USA and the UK. This paper provides calculations of average marginal tax rates for the four Scandinavian countries using the methodologies of Seater (1982,1985) and Barro and Sahasakul (1983, 1986). Then, by pooling the newly calculated tax rates for the Scandinavian countries with the data for the USA and the UK, we investigate the effects of tax policy shocks on the per capita GDP growth rate. Our results suggest that an increase in average marginal tax rates has a negative impact on economic growth. Employing additive mixed panel models with penalized splines as estimation approach, we show that changes in tax rates have nonlinear effects. Increasing average marginal tax rates turn out to be the most distorting at relatively moderate tax rates. Copyright © 2013 John Wiley & Sons, Ltd.

This paper estimates the effects of unilateral divorce laws on divorce rates in the USA from a panel of state-level divorce rates. We use the interactive fixed-effects model to address the issue of endogeneity due to the association between cross-state unobserved heterogeneity and divorce law reforms. We document that earlier studies in the literature do not fully control for unobserved heterogeneity and result in mixed empirical evidence on the effects of divorce law reforms. While reconciling these conflicting results, our results suggest that divorce law reforms have temporal positive effects on divorce rates, thus confirming the 2006 findings of Wolfers. Via simulation experiments, we assess the degree to which faulty inclusion or faulty exclusion of interactive fixed effects affects the policy effect estimators. Our results suggest that faulty inclusion only results in efficiency loss whereas faulty exclusion causes bias. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper we modify the expectation maximization algorithm in order to estimate the parameters of the dynamic factor model on a dataset with an arbitrary pattern of missing data. We also extend the model to the case with a serially correlated idiosyncratic component. The framework allows us to handle efficiently and in an automatic manner sets of indicators characterized by different publication delays, frequencies and sample lengths. This can be relevant, for example, for young economies for which many indicators have been compiled only recently. We evaluate the methodology in a Monte Carlo experiment and we apply it to nowcasting of the euro area gross domestic product. Copyright © 2012 John Wiley & Sons, Ltd.

We use a macro-finance model, incorporating macroeconomic and financial factors, to study the term premium in the US bond market. Estimating the model using Bayesian techniques, we find that a single factor explains most of the variation in bond risk premiums. Furthermore, the model-implied risk premiums account for up to 40% of the variability of one- and two-year excess returns. Using the model to decompose yield spreads into an expectations and a term premium component, we find that, although this decomposition does not seem important to forecast economic activity, it is crucial to forecast inflation for most forecasting horizons. Copyright © 2012 John Wiley & Sons, Ltd.

This paper considers a panel data stochastic frontier model that disentangles unobserved firm effects (firm heterogeneity) from persistent (time-invariant/long-term) and transient (time-varying/short-term) technical inefficiency. The model gives us a four-way error component model, viz., persistent and time-varying inefficiency, random firm effects and noise. We use Bayesian methods of inference to provide robust and efficient methods of estimating inefficiency components in this four-way error component model. Monte Carlo results are provided to validate its performance. We also present results from an empirical application that uses a large panel of US commercial banks. Copyright © 2012 John Wiley & Sons, Ltd.

When modeling demand for differentiated products, it is vital to adequately capture consumer taste heterogeneity, But there is no clearly preferred approach. Here, we compare the performance of six alternative models. Currently, the most popular are mixed logit (MIXL), particularly the version with normal mixing (N-MIXL), and latent class (LC), which assumes discrete consumer types. Recently, several alternative models have been developed. The 'generalized multinomial logit' (G-MNL) extends N-MIXL by allowing for heterogeneity in the logit scale coefficient. Scale heterogeneity logit (S-MNL) is a special case of G-MNL with scale heterogeneity only. The 'mixed-mixed' logit (MM-MNL) assumes a discrete mixture-of-normals heterogeneity distribution. Finally, one can modify N-MIXL by imposing theoretical sign constraints on vertical attributes. We call this 'T-MIXL'. We find that none of these models dominates the others, but G-MNL, MM-MNL and T-MIXL typically outperform the popular N-MIXL and LC models. Copyright © 2012 John Wiley & Sons, Ltd.

Financial time series are often non-negative-valued (volumes, trades, durations, realized volatility, daily range) and exhibit clustering. When joint dynamics is of interest, the vector multiplicative error model (vMEM; the element-by-element product of a vector of conditionally autoregressive scale factors and a multivariate i.i.d. innovation process) is a suitable strategy. Its parameters can be estimated by generalized method of moments, bypassing the problem of specifying a multivariate distribution for the errors. Simulated results show the gains in efficiency relative to an equation-by-equation approach. A vMEM on several measures of volatility justifies a joint approach revealing full interdependence. Copyright © 2012 John Wiley & Sons, Ltd.

We calculate, by simulations, numerical asymptotic distribution functions of likelihood ratio tests for fractional unit roots and cointegration rank. Because these distributions depend on a real-valued parameter b which must be estimated, simple tabulation is not feasible. Partly owing to the presence of this parameter, the choice of model specification for the response surface regressions used to obtain the numerical distribution functions is more involved than is usually the case. We deal with model uncertainty by model averaging rather than by model selection. We make available a computer program which, given the dimension of the problem, q, and a value of b, provides either a set of critical values or the asymptotic P-value for any value of the likelihood ratio statistic. Copyright © 2012 John Wiley & Sons, Ltd.

This paper estimates a dynamic ordered probit model of self-assessed health with two fixed effects: one in the linear index equation and one in the cut-points. This robustly controls for heterogeneity in unobserved health status and in reporting behavior, although we cannot separate both sources of heterogeneity. We find important state dependence effects, and small but significant effects of income and other socioeconomic variables. Having dynamics and flexibly accounting for unobserved heterogeneity matters for those estimates. We also contribute to the bias correction literature in nonlinear panel models by comparing and applying two of the existing proposals to our model. Copyright © 2012 John Wiley & Sons, Ltd.

Recently, Duarte and Young (2009) studied the probability of informed trading (PIN) proposed by Easley et al. (2002) and decomposed it into two parts: the adjusted PIN (APIN) as a measure of asymmetric information and the probability of symmetric order-flow shock (PSOS) as a measure of illiquidity. They provide some cross-section estimates of these measures using daily data over annual periods. In this paper we propose a method to estimate daily APIN and PSOS by extending the method in Tay et al. (2009) using high-frequency transaction data. Our empirical results show that while PIN is positively contemporaneously correlated with variance, APIN is not. On the other hand, PSOS is positively correlated with daily average effective spread and variance, which is consistent with the interpretation of PSOS as a measure of illiquidity. Compared to APIN, PSOS exhibits clustering and sporadic bursts over time. Copyright © 2012 John Wiley & Sons, Ltd.

We provide the first empirical application of a new approach proposed by Lee (Journal of Econometrics 2007; 140(2), 333–374) to estimate peer effects in a linear-in-means model when individuals interact in groups. Assumingsufficient group size variation, this approach allows to control for correlated effects at the group level and to solve the simultaneity (reflection) problem. We clarify the intuition behind identification of peer effects in the model. We investigate peer effects in student achievement in French, Science, Mathematics and History in secondary schools in the Province of Québec (Canada). We estimate the model using conditional maximum likelihood and instrumental variables methods. We find some evidence of peer effects. The endogenous peer effect is large and significant in Mathematics but imprecisely estimated in the other subjects. Some contextual peer effects are also significant. In particular, for most subjects, the average age of peers has a negative effect on own test score. Using calibrated Monte Carlo simulations, we find that high dispersion in group sizes helps with potential issues of weak identification. Copyright © 2012 John Wiley & Sons, Ltd.

This paper develops a long-run output relation for a major oil-exporting economy where the oil income-to-output ratio remains sufficiently high over a prolonged period. It extends the stochastic growth model developed in Binder and Pesaran (1999) by including oil exports as an additional factor in the capital accumulation process. The paper distinguishes between the two cases where the growth of oil income, g^o, is less than the natural growth rate (the sum of the population growth, n, and the growth of technical progress, g), and when g^o ≥ g + n. Under the former, the effects of oil income on the economy's steady growth rate will vanish eventually, while under the latter oil income enters the long-run output equation with a coefficient which is equal to the share of capital if it is further assumed that the underlying production technology can be represented by a Cobb–Douglas production function. The long-run theory is tested using quarterly data on nine major oil economies. Overall, the test results support the long-run theory, with the existence of long-run relations between real output, foreign output and real oil income established for six of the nine economies considered. Copyright © 2012 John Wiley & Sons, Ltd.

Vector autoregressive methods have been used to model the interrelationships between job vacancy rates, job separation rates and job-finding rates using tools such as impulse response analysis. We investigate whether such impulse responses change across the business cycle or over time, by estimating time-varying parameter–vector autoregressions for data from North America (the USA and Canada) and Europe (France, Spain and the UK). While the adjustment process of the labour market to shocks in Canada and the USA is similar, we find the adjustment process differs much more across the European countries, with greater persistence in shocks relative to the USA and Canada. Copyright © 2012 John Wiley & Sons, Ltd.

Using parametric and non-parametric estimation techniques, we analyze the sustainability of the recently growing current account imbalances in the euro area and test whether the European Monetary Union has aggravated these imbalances. Two alternative criteria for the assessment of external debt sustainability are considered: one based on the transversality condition of intertemporal optimization, and the other based on the stationarity properties of the stochastic process of the debt–GDP ratio. Econometric sustainability tests are performed using the pooled mean-group estimator and panel unit root tests, respectively. Variants of both test procedures with varying coefficients using penalized splines estimation are applied. We find empirical evidence suggesting that the introduction of the euro is associated with a regime shift from sustainability to unsustainability of external debt accumulation for the euro area. Copyright © 2012 John Wiley & Sons, Ltd.

There has been a systematic increase in the volatility of the real price of crude oil since 1986, followed by a decline in the volatility of oil production since the early 1990s. We explore reasons for this evolution. We show that a likely explanation of this empirical fact is that both the short-run price elasticities of oil demand and of oil supply have declined considerably since the second half of the 1980s. This implies that small disturbances on either side of the oil market can generate large price responses without large quantity movements, which helps explain the latest run-up and subsequent collapse in the price of oil. Our analysis suggests that the variability of oil demand and supply shocks actually has decreased in the more recent past, preventing even larger oil price fluctuations than observed in the data. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, we introduce a Bayesian panel probit model with two flexible latent effects: first, unobserved individual heterogeneity that is allowed to vary in the population according to a nonparametric distribution; and second, a latent serially correlated common error component. In doing so, we extend the approach developed in Albert and Chib (Journal of the American Statistical Association 1993; 88: 669–679; in Bayesian Biostatistics, Berry DA, Stangl DK (eds), Marcel Dekker: New York, 1996), and in Chib and Carlin (Statistics and Computing 1999; 9: 17–26) by releasing restrictive parametric assumptions on the latent individual effect and eliminating potential spurious state dependence with latent time effects. The model is found to outperform more traditional approaches in an extensive series of Monte Carlo simulations. We then apply the model to the estimation of a patent equation using firm-level data on research and development (R&D). We find a strong effect of technology spillovers on R&D but little evidence of product market spillovers, consistent with economic theory. The distribution of latent firm effects is found to have a multimodal structure featuring within-industry firm clustering. Copyright © 2012 John Wiley & Sons, Ltd.

This paper studies the estimation of the distribution of non-sequential search costs. We show that the search cost distribution is identified by combining data from multiple markets with common search technology but varying consumer valuations, firms' costs, and numbers of competitors. To exploit such data optimally, we provide a new method based on semi-nonparametric estimation. We apply our method to a dataset of online prices for memory chips and find that the search cost density is essentially bimodal, such that a large fraction of consumers searches very little, whereas a smaller fraction searches a relatively large number of stores. Copyright © 2012 John Wiley & Sons, Ltd.

This paper provides a comprehensive evaluation of the effects of benefit sanctions on post-unemployment outcomes such as post-unemployment employment stability and earnings. We use rich register data which allow us to distinguish between a warning that a benefit reduction may take place in the near future and the actual withdrawal of unemployment benefits. Adopting a multivariate mixed proportional hazard approach to address selectivity, we find that warnings do not affect subsequent employment stability but do reduce post-unemployment earnings. Actual benefit reductions lower the quality of post-unemployment jobs both in terms of job duration as well as in terms of earnings. Copyright © 2012 John Wiley & Sons, Ltd.

We study the workings of the factor analysis of high-dimensional data using artificial series generated from a large, multi-sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allows us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of diffusion index forecasts, and assess the quality of the factor analysis of highly disaggregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model. Copyright © 2012 John Wiley & Sons, Ltd.

Conditional heteroskedasticity, skewness and leverage effects are well-known features of financial returns. The literature on factor models has often made assumptions that preclude the three effects to occur simultaneously. In this paper I propose a conditionally heteroskedastic factor model that takes into account the presence of both the conditional skewness and leverage effects. This model is specified in terms of conditional moment restrictions and unconditional moment conditions are proposed allowing inference by the generalized method of moments (GMM). The model is also shown to be closed under temporal aggregation. An application to daily excess returns on sectorial indices from the UK stock market provides strong evidence for dynamic conditional skewness and leverage with a sharp efficiency gain resulting from accounting for both effects. The estimated volatilitypersistence from the proposed model is lower than that estimated from models that rule out such effects. I also find that the longer the returns' horizon, the fewer conditionally heteroskedastic factors may be required for suitable modeling and the less strong is the evidence for dynamic leverage. Some of these results are in line with the main findings of Harvey and Siddique (1999) and Jondeau and Rockinger (2003), namely that accounting for conditional skewness impacts the persistence in the conditional variance of the return process. Copyright © 2012 John Wiley & Sons, Ltd.

The increase in childhood obesity has garnered the attention of many in policymaking circles. Consequently, school nutrition programs such as the School Breakfast Program (SBP) have come under scrutiny. The identification of the causal effects of such programs, however, is difficult owing to non-random selection into the program and the lack of exclusion restrictions. Here, we propose two new estimators aimed at addressing this situation. We compare our new estimators to existing approaches using simulated data. We show that while correlations might suggest that SBP causes childhood obesity, SBP is likely to reduce childhood obesity once selection is addressed. Copyright © 2012 John Wiley & Sons, Ltd.

This paper introduces a quasi maximum likelihood approach based on the central difference Kalman filter to estimate non-linear dynamic stochastic general equilibrium (DSGE) models with potentially non-Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models solved up to third order. These properties are verified in a Monte Carlo study for a DSGE model solved to second and third order with structural shocks that are Gaussian, Laplace distributed, or display stochastic volatility. Copyright © 2012 John Wiley & Sons, Ltd.

We model the dynamic volatility and correlation structure of electricity futures of the European Energy Exchange index. We use a new multiplicative dynamic conditional correlation (mDCC) model to separate long-run from short-run components. We allow for smooth changes in the unconditional volatilities and correlations through a multiplicative component that we estimate nonparametrically. For the short-run dynamics, we use a GJR-GARCH model for the conditional variances and augmented DCC models for the conditional correlations. We also introduce exogenous variables to account for congestion and delivery date effects in short-term conditional variances. We find different correlation dynamics for long- and short-term contracts and the new model achieves higher forecasting performance compared \to a standard DCC model. Copyright © 2012 John Wiley & Sons, Ltd.

This paper presents a structural estimation of a life cycle model with unemployment risk. The model allows for human capital depreciation during unemployment. It is estimated using German and US household-level data. The data suggest that the adverse impact of unemployment on individual productivity is important in both countries, but quantitatively more relevant in Germany. Moreover, simulations show that the combination of skill depreciation with the generous unemployment insurance system that was in place in Germany until recently is a key factor in explaining the differences in labour market performance between these countries. Copyright © 2012 John Wiley & Sons, Ltd.

We quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich dataset from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The preferred model suggests that the probability of a member making a full repayment would be 12 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity. Copyright © 2012 John Wiley & Sons, Ltd.

This paper proposes Bayesian forecasting in a vector autoregression using a democratic prior. This prior is chosen to match the predictions of survey respondents. In particular, the unconditional mean for each series in the vector autoregression is centered around long-horizon survey forecasts. Heavy shrinkage toward the democratic prior is found to give good real-time predictions of a range of macroeconomic variables, as these survey projections are good at quickly capturing endpoint shifts. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, I investigate Samuelson's low-price auction model with entry costs. The model's equilibrium implies that the distribution of bids is truncated at the threshold for participation. I use the model to estimate the cost of participation in Michigan highway procurement auctions. The null hypothesis of zero entry costs is rejected. Using my empirical results, I then construct an estimate of the optimal auction, which employs regular policy tools such as entry fees. Finally, I demonstrate the savings that the Michigan government could have made on payments if optimal auctions had been employed. Copyright © 2012 John Wiley & Sons, Ltd.

This paper presents a model that provides conditions under which a causal interpretation can be given to the association between childhood parental employment and subsequent educational attainments of children. The key parameter comes from theconditional demand function for children's future earning capacity. Its identification rests on having data on siblings and assumptions about the timing of parents' knowledge of their children's endowments. In addition to sibling differences, the useof a fixed-effects instrumental-variables estimator identifies the parameter under weaker conditions. Empirical analysis informed by the model reveals a negative and significant effect on the child's educational attainment of the months of the mother's full-time employment when the child was aged 0–5. The effect of the mother's part-time employment is smaller and less well determined, but again negative. These results suggest that the substitution effect of the mother's employment dominates the income effects. Stronger adverse effects are found for children of less-educated mothers. Copyright © 2012 John Wiley & Sons, Ltd.

We propose a class of observation-driven time series models referred to as generalized autoregressive score (GAS) models. The mechanism to update the parameters over time is the scaled score of the likelihood function. This new approach provides a unified and consistent framework for introducing time-varying parameters in a wide class of nonlinear models. The GAS model encompasses other well-known models such as the generalized autoregressive conditional heteroskedasticity, autoregressive conditional duration, autoregressive conditional intensity, and Poisson count models with time-varying mean. In addition, our approach can lead to new formulations of observation-driven models. We illustrate our framework by introducing new model specifications for time-varying copula functions and for multivariate point processes with time-varying parameters. We study the models in detail and provide simulation and empirical evidence. Copyright © 2012 John Wiley & Sons, Ltd.

This paper models for the first time a spatial process in local tax policies in the presence of centrally imposed fiscal limitations. Focusing on the frequently encountered case of a tax rate cap, we evaluate three empirical approaches to the analysis of spatially dependent limited tax policies: (i) a Bayesian spatial approach for censored dependent variables; (ii) a Tobit corner solution model augmented with a spatial lag; (iii) a spatial discrete hazard model. The evidence arising from an investigation of severely state-constrained local vehicle taxes in Italy suggests that ignoring tax limitations can lead to substantial underestimation of inter-jurisdictional fiscal interaction. Copyright © 2011 John Wiley & Sons, Ltd.

Medical expenses are an increasingly important contributor to household financial risk. We examine the effect of medical expenditure risk on the willingness of Medicare beneficiaries to hold risky assets. Using a discrete-factor maximum likelihood method to address the endogeneity of insurance choices, we find that having a moderately protective Medigap or employer supplemental policy increases risky asset holding by 7.1 percentage points relative to those without supplemental coverage, while participation in a highly protective Medicare health maintenance organization increases risky asset holding by 13.0 percentage points. Our results highlight an important link between the availability of health insurance and financial behavior. Copyright © 2012 John Wiley & Sons, Ltd.

Semiparametric varying-coefficient models have become a common fixture in applied data analysis. Existing approaches, however, presume that those variables affecting the coefficients are continuous in nature (or that there exists at least one such continuous variable) which is often not the case. Furthermore, when all variables affecting the coefficients are categorical/discrete, theoretical underpinnings cannot be obtained as a special case of existing approaches and, as such, requires a separate treatment. In this paper we use kernel-based methods that place minimal structure on the underlying mechanism governing parameter variation across categorical variables while providing a consistent and efficient approach that may be of interest to practitioners. One area where such models could be particularly useful is in settings where interactions among the categorical and real-valued predictors consume many (or even exhaust) degrees of freedom for fully parametric models (which is frequently the case in applied settings). Furthermore, we demonstrate that our approach behaves optimally when in fact there is no variation in a model's coefficients across one or more of the categorical variables (i.e. the approach pools over such variables with a high probability). An illustrative application demonstrates potential benefits for applied researchers. Copyright © 2011 John Wiley & Sons, Ltd.

Qualitative business survey data are used widely to provide indicators of economic activity ahead of the publication of official data. Traditional indicators exploit only aggregate survey information, namely the proportions of respondents who report ‘up’ and ‘down’. This paper examines disaggregate or firm-level survey responses. It considers how the responses of the individual firms should be quantified and combined if the aim is to produce an early indication of official output data. Having linked firms' categorical responses to official data using ordered discrete-choice models, the paper proposes a statistically efficient means of combining the disparate estimates of aggregate output growth which can be constructed from the responses of individual firms. An application to firm-level survey data from the Confederation of British Industry shows that the proposed indicator can provide early estimates of output growth more accurately than traditional indicators. Copyright © 2012 John Wiley & Sons, Ltd.

We use a sharp discontinuity in the maximum duration of benefit entitlement to identify the effect of extended benefit duration on unemployment duration and post-unemployment outcomes (employment stability and re-employment wages). We address dynamic selection, which may arise even under an initially random assignment to treatment, estimating a bivariate discrete-time hazard model jointly with a wage equation and correlated unobservables. Owing to the non-stationarity of job search behavior, we find heterogeneous effects of extended benefit duration on the re-employment hazard and on job match quality. Our results suggest that the unemployed who find a job close to and after benefit exhaustion experience less stable employment patterns and receive lower re-employment wages compared to their counterparts who receive extended benefits and exit unemployment in the same period. These results are found to be significant for men but not for women. Copyright © 2012 John Wiley & Sons, Ltd.

We estimate the effect of cash transfers given to youth conditional on high school attendance on the labor supply decisions and academic performance of youth. We exploit differences in the size of the total transfer received based on timing of birth to identify the causal effects of interest. Specifically, individuals born late in a quarter receive a larger total transfer than comparable individuals born early in the following quarter. We find that the transfer increases the labor market participation of youth and the number of months worked. The estimated effect is larger for individuals from low-income families. The results suggest that some youths are borrowing constrained. Since we find no evidence of corresponding effects on academic performance, alleviating the constraint appears only to affect consumption decisions and not human capital investment. Copyright © 2011 John Wiley & Sons, Ltd.

In the spatial model of voting, voters choose the candidate closest to them in the ideological space. Recent work by Degan and Merlo in 2009 shows that it is falsifiable on the basis of individual voting data in multiple elections. We show how to tackle the fact that the model only partially identifies the distribution of voting profiles and we give a formal revealed preference test of the spatial voting model in three national elections in the USA, and strongly reject the spatial model in all cases. We also construct confidence regions for partially identified voter characteristics in an augmented model with unobserved valence dimension, and identify the amount of voter heterogeneity necessary to reconcile the data with spatial preferences. Copyright © 2011 John Wiley & Sons, Ltd.

We study entry into pharmaceutical submarkets by using a dynamic panel probit model. We develop a Bayesian version of Wooldridge's approach to dealing with unobserved heterogeneity. We distinguish between greenfield entry (entry with first product) and undifferentiated entry, which may take the form of introducing further products. We extend the standard reduced form model to consider company size in the submarket and across all submarkets. We find that greenfield and undifferentiated entries have different determinants, that global and submarket size measures have different effects and that sunk costs often have positive effects on entry due to a commitment mechanism. Copyright © 2012 John Wiley & Sons, Ltd.

Competition across space can be fundamentally altered by changes in market institutions. We propose a framework that integrates market-altering policy changes in the spatial analysis of competitive behavior and incorporates endogenous breaks in explanatory variables for spatial panel datasets. This paper fills a gap in the literature between work focusing on spatial price responsiveness of agents and work on changes in market regulations that affect competition. We apply the framework to an important current fishery management policy to explore how a change from aggregate to individual fishing quotas affects the spatial price responsiveness of fish processors. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper we put forward a Bayesian model averaging method aimed at performing inference under model uncertainty in the presence of potential spatial autocorrelation. The method uses spatial filtering in order to account for uncertainty in spatial linkages. Our procedure is applied to a dataset of income per capita growth and 50 potential determinants for 255 NUTS-2 European regions. We show that ignoring uncertainty in the type of spatial weight matrix can have an important effect on the estimates of the parameters attached to the model covariates. After integrating out the uncertainty implied by the choice of regressors and spatial links, human capital investments and transitional dynamics related to income convergence appear as the most robust determinants of growth at the regional level in Europe. Our results imply that a quantitatively important part of the income convergence process in Europe is influenced by spatially correlated growth spillovers. Copyright © 2012 John Wiley & Sons, Ltd.