The FMLS-based CUSUM statistic for testing the null of smooth time-varying cointegration in the presence of a structural break

In this paper we extend the FMLS-based CUSUM cointegration test (Xiao and Phillips, 2002) for testing the smooth time-varying cointegration null hypothesis. For this purpose we use Chebyshev time polynomials to specify time-varying coefficients under the null. We derive the limiting distribution of the statistic, which is pivotal with the order of the Chebyshev time polynomials, and we provide the critical values to conduct the proposed test.     

Testing for structural breaks with local smoothers: A simulation study

By means of an extensive Monte Carlo simulation study based on the design of Chen and Hong (2012) we compare the performance of the tests they proposed for parameter stability with the linearity test of Li et al. (2002) and the functional form test of Li and Wang (1998). We find that the test of Li et al. (2002) test adapted to testing for parameter stability performs favorably well in terms of size and equally well in terms of power compared with the others, whereas the test by Li and Wang has no power.     

Exploring the effects of aggregation error in the estimation of consumer demand elasticities

Errors introduced by using aggregate data in estimating a consumer demand model have long been a concern. We study the effects of such errors on elasticity estimates derived from AIDS and QUAIDS models. Based on a survey of published articles, a generic parameterization of the income distribution, and the range of Gini coefficients reported for 28 OECD countries, we generate and analyze a large number of “observations” on the differences between elasticities calculated at the aggregate level and those calculated at the micro level. We suggest a procedure for evaluating the likely range of aggregation error when a model is estimated with aggregate data.     

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.     

Testing for efficiency in selected developing foreign exchange markets: An equilibrium-based approach

This paper proposes an alternative way of testing FOREX efficiency for developing countries. The FOREX market will be efficient if fully reflects all available information. If this holds, the actual exchange rate will not deviate significantly from its equilibrium rate. Moreover, the spot rate should deviate from its equilibrium rate by only transitory components (i.e. it should follow a white noise process). This test is applied to three Central and Eastern European Countries — members of the EU. Considering an LSTAR model we find no evidence of nonlinear adjustment in the misalignment series. So, linear unit root tests imply that the Poland/Euro FOREX market is efficient, the Czech/Euro FOREX market is not, while the Slovak/Euro FOREX market is quasi-efficient.     

Alcohol content and demand for alcoholic beverages: A system approach

This paper examines how alcohol content affects the consumption of alcoholic beverages in Finland. Three different quality hypotheses are studied and compared: Fisher and Shell, Theil, and an additive one. The comparison of the hypotheses is based on quality elasticities implied by the hypotheses. The results show that, under all hypotheses, alcohol content positively affects the demand for alcoholic beverages, and this effect depends negatively on income. The results of the comparison of the hypotheses show that the additive fits the data best. However, the other hypotheses are almost as good: Fisher and Shell's hypothesis better than Theil's.I would like to thank K. Koskela, A. Nyberg, M. Salo, M. Stenius, and I. Suoniemi for their useful comments and suggestions. The author bears sole responsibility for any remaining errors.     

Testing the growth effects of structural change

Against the backdrop of Baumol's model of ‘unbalanced growth’, a recent strand of literature has presented models that manage to reconcile structural change with Kaldor's ‘stylized fact’ of the relative constancy of per-capita real GDP growth. Another strand of literature goes beyond this, arguing that the expenditure shifts toward Baumol's ‘stagnant’ sector stimulate rather than dampen long-term economic growth because of the human capital-accumulating nature of major ‘stagnant’ services (like health care and education). This paper tests the relationship between structural change and economic growth empirically by means of a Granger-causality analysis of a panel of 18 OECD countries.     

Carbon tax simulations using a household demand model

The main objective of this paper is to analyse consumer response and welfare effects due to changes in energy or environmental policy. To achieve this objective we formulate and estimate an econometric model for non-durable consumer demand in Sweden that utilises micro- and macro-data. In the simulations, we consider two revenue neutral scenarios that both imply a doubling of the CO₂ tax; one that returns the revenues in the form of a lower VAT and one that subsidise public transport. One conclusion from the simulations is that the CO₂ tax has regional distribution effects, in the sense that household living in sparsely populated areas carry a larger share of the tax burden.     

On testing for nonlinearity in multivariate time series

This paper considers a multivariate extension of the test for neglected nonlinearity proposed by Tsay (1986) that uses principal components to overcome the problem of dimensionality that is common with tests of this type. Monte Carlo experiments reveal that the modified multivariate test provides a significant dimensional reduction without suffering from any systematic level distortion or power loss, and is more powerful than univariate nonlinearity tests.     

On the Fisher information matrix of a vector ARMA process

We derive a neat and compact representation of the asymptotic Fisher information matrix of a vector ARMA process. Its inverse can be used immediately as the asymptotic covariance matrix of the Gaussian maximum likelihood estimator. We also provide the robust sandwich covariance estimator when the process is non-Gaussian.     

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.     

A simple unit root test against asymmetric STAR nonlinearity with an application to real exchange rates in Nordic countries

Existing tests of the unit root hypothesis against the alternative hypothesis of exponential smooth transition autoregressive (ESTAR) nonlinearity implicitly assume symmetry under the alternative. This paper proposes a simple unit root test against the alternative of symmetric or asymmetric ESTAR nonlinearity. In the event that the unit root hypothesis is rejected, a simple test of symmetric versus asymmetric ESTAR nonlinearity is also proposed. The asymptotic distributions of the test statistics are straightforward to establish and finite-sample performance is studied with Monte Carlo simulations. An empirical application involving the real exchange rates of four Nordic countries against the U.S. dollar illustrates the usefulness of the new tests.     

Testing Prediction Performance of Poverty Models: Empirical Evidence from Uganda

This paper examines the performance of a method of predicting poverty rates. Because most developing countries cannot justify the expense of frequent household budget surveys, additional low‐cost methods have been developed and used. The prediction method is based on a model linking the proportion of poor households to suitable explanatory variables (consumption proxies). These consumption proxies are variables that can be collected at much lower cost through smaller annual surveys. Several applications have shown that such models can produce poverty estimates with confidence intervals of a similar magnitude to the poverty estimates from the household budget surveys. There is, however, limited evidence of how well the methods perform out‐of‐sample. A series of seven household budget surveys conducted in Uganda in the period 1993–2005 allows us to test the prediction performance of the model. We test the poverty models by using data from one survey to predict the proportion of poor households in other surveys, and vice versa. The results are encouraging, as all models predict similar poverty trends. Although in most cases the predictions are precise, sometimes they differ significantly from the poverty level estimated from the survey directly.     

Testing the validity of the monetary model for ASEAN with structural break

This study examines the validity of the long run structural relations underlying the monetary exchange rate model for Malaysia, Singapore, The Philippines and Thailand. Take into consideration the possibility of structural change, we examined the models using recent developed techniques of testing unit root and cointegration with a structural break. Our findings of three cointegrating relations among the variables in the system were further identified by testing theoretical restrictions on the cointegrating equations. The long run relationships were able to be interpreted according to the theory, hence, support the long run validity of the monetary exchange rate model.     

Testing slope homogeneity in large panels with serial correlation

Pesaran and Yamagata (Pesaran, M.H., Yamagata, T., Testing slope homogeneity in large panels, Journal of Econometrics 142, 50–93, 2008) propose a test for slope homogeneity in large panels, which has become very popular in the literature. However, the test cannot deal with the practically relevant case of heteroskedastic and/serially correlated errors. The present note proposes a generalized test that accommodates both features.     

A method for finding the maximal set in excess demand

We present a polynomial time method for identifying the maximal set in excess demand at a given payoff vector. This set can be used in “large” partnership formation problems to identify the minimum element in the set of individually rational payoff vectors at which there is no overdemanded set of agents. This minimum element corresponds to the minimum Walrasian equilibrium price vector in a special case of the partnership formation problem.     

Testing of the mean reversion parameter in continuous time models

In this paper we use the approximate bias expressions developed in Yu (2012) and Bao et al. (2013) to improve the testing of the ordinary least squares or quasi-maximum likelihood estimator of the mean reversion parameter in continuous time models. We follow the approach given in Iglesias and Phillips (2005) and Chambers (2013), where if we bias correct the estimated mean reversion parameter, we can improve on the small sample properties of the testing procedure. Simulation results confirm the usefulness of this approach using a t$t$-statistic in this setting in the near unit root situation when the mean reversion parameter is approaching its lower bound. Therefore we always recommend bias correcting when applying a t$t$-statistic in practice in this context.     

On the distributional effects of income in an aggregate consumption relation

Abstract .  In this paper we analyse the influence of characteristics of the income distribution in modelling aggregate consumption expenditure. We model the aggregate consumption relation of a heterogeneous population, using a statistical distributional approach of aggregation, and apply it to UK-Family Expenditure Survey data. A bootstrap test based on a non-parametric estimation methodology, which accounts for the presence of continuous and discrete variables, suggests that the mean and the dispersion of the income distribution significantly influence aggregate consumption expenditure. Also, the parameters of the aggregate relation are time varying. These findings have implications for constructing empirically sound models of aggregate consumption expenditure.     

Testing for normality in linear regression models using regression and scale equivariant estimators

In this paper we provide a general solution to the problem of controlling the probability of a type I error in normality tests for the disturbances in linear regressions when using robust-regression residuals. We show that many classes of well-known robust regression estimators belong to the class of regression and scale equivariant estimators. It is these equivariance properties that are used to reduce the nuisance parameter space under the null, from which we develop Monte Carlo and Maximized Monte Carlo tests for the null of disturbance normality. Finally, we illustrate in a simulation experiment the potential power gains from using robust-regression residuals in testing this null hypothesis.     

Improving consumption measurement and other survey data through CAPI: Evidence from a randomized experiment

This paper reports on a randomized survey experiment among 1840 households, designed to compare pen-and-paper interviewing (PAPI) to computer-assisted personal interviewing (CAPI). We find that PAPI data contain a large number of errors, which can be avoided in CAPI. Error counts are not randomly distributed across the sample, but are correlated with household characteristics, potentially introducing sample bias if dubious observations need to be dropped. We demonstrate a tendency for the spread of total measured consumption to be higher on paper compared to CAPI, translating into significantly higher measured inequality. Investigating further the nature of PAPI's measurement error for consumption, we fail to reject the hypothesis that it is classical: it attenuates the coefficient on consumption when used as explanatory variable and we find no evidence of bias when consumption is used as dependent variable. Finally, CAPI and PAPI are compared in terms of interview length, costs and respondents' perceptions.