Testing for parameter restrictions in a stationary VAR model: A bootstrap alternative

This paper proposes the use of the bootstrap when the system Wald test is employed to test for linear restrictions in a stationary vector autoregressive (VAR) model. The bootstrap test is conducted using the estimated generalised least square estimator for VAR parameters, which considers contemporaneous correlations among the error terms. It is found that the bootstrap test shows little size distortion in small samples. In contrast, the asymptotic Wald test exhibits serious size distortion, severely over-rejecting the true null hypothesis in small samples. The bootstrap test also has desirable power properties, with its power particularly high when the model is near non-stationary and the error terms are highly correlated contemporaneously. As an application, the bootstrap Wald test is employed to test for the predictability of stock return from dividend yield using U.S. data.     

The Box-Cox transformation-of-variables in regression

The application of the Box-Cox transformation to the dependent and independent variables is discussed. Maximum likelihood and iterative GLS estimators are used and bootstrapping is carried out to compare the bootstrap sample variability with the finite sample variability (RMSE) and improve RMSE estimation. The biases of parameter estimators were shown to be substantial in small samples. The standard errors obtained from the Hessian matrix were a poor measure of the finite sample variability. Thet-ratios of the linear parameter estimators may not be normally distributed in small samples.The authors acknowledge the helpful comments of two referees.     

Moran's I test of spatial panel data model — Based on bootstrap method

Under the condition of the finite sample or the unknown distributed error term, testing for spatial dependence in panel data models is an unresolved problem in spatial econometrics. In this paper, a fast double bootstrap (FDB) method is used to construct bootstrap Moran's I tests for Moran's I test in spatial panel data models, and Monte Carlo simulation experiments are used to prove the effectiveness from two aspects including size distortion and power. The experiment results show that, in asymptotic Moran's I test, there is serious size distortion, which could be rectified in bootstrap Moran's I test.     

NONPARAMETRIC BOOTSTRAP PROCEDURES FOR PREDICTIVE INFERENCE BASED ON RECURSIVE ESTIMATION SCHEMES*

We introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one application, we outline a consistent test for out‐of‐sample nonlinear Granger causality, and in the other we outline a test for selecting among multiple alternative forecasting models, all of which are possibly misspecified. In a Monte Carlo investigation, we compare the finite sample properties of our block bootstrap procedures with the parametric bootstrap due to Kilian (Journal of Applied Econometrics 14 (1999), 491–510), within the context of encompassing and predictive accuracy tests. In the empirical illustration, it is found that unemployment has nonlinear marginal predictive content for inflation.     

Empirical likelihood confidence intervals for the Gini measure of income inequality

Gini coefficient is among the most popular and widely used measures of income inequality in economic studies, with various extensions and applications in finance and other related areas. This paper studies confidence intervals on the Gini coefficient for simple random samples, using normal approximation, bootstrap percentile, bootstrap-t and the empirical likelihood method. Through both theory and simulation studies it is shown that the intervals based on normal or bootstrap approximation are less satisfactory for samples of small or moderate size than the bootstrap-calibrated empirical likelihood ratio confidence intervals which perform well for all sample sizes. Results for stratified random sampling are also presented.     

Income convergence clubs for Brazilian Municipalities: a non-parametric analysis

This article analyses the evolution of relative per capita income distribution of Brazilian municipalities over the period 1970–1996. Analyses are based on non-parametric methodologies and do not assume probability distributions or functional forms for the data. Two convergence tests have been carried out – a test for sigma convergence based on the bootstrap principle and a beta convergence test using smoothing splines for the growth regressions. The results obtained demonstrate the need to model the dynamics of income for Brazilian municipalities as a process of convergence clubs, using the methodology of transition matrices and stochastic kernels. The results show the formation of two convergence clubs, a low income club formed by the municipalities of the North and Northeast regions, and another high income club formed by the municipalities of the Center-West, Southeast and South regions. The formation of convergence clubs is confirmed by a bootstrap test for multimodality.     

The export-output growth nexus in Japan: a bootstrap rolling window approach

The purpose of this article is to examine the export–output nexus in Japan by taking into account the time variation in the causal link with bootstrap Granger non-causality test and rolling estimation. The data used cover the seasonally adjusted real export and real Gross Domestic Product (GDP) for the 1957:1–2009:1 period. Standard Granger causality tests indicate no causality between export and real GDP series. On the contrary, full sample-modified Granger causality tests based on bootstrap, which are applicable irrespective of integration–cointegration properties of the data, indicate a bi-directional causal link between exports and real GDP. Accordingly, export growth should be an important factor behind Japan’s high-economic growth in the last three decades. Using parameter stability tests, we show that these results are not uniform for different sample periods and results vary due to structural changes. Using bootstrap rolling window estimation, we find that there is a positive bi-directional predictive power from the mid 1970s to the late-1980s between the series, while from the late 1990s to 2009 there is a positive predictive power only from export growth to output growth.     

A smooth coefficient quantile regression approach to the social capital–economic growth nexus

This analysis assesses the role of social capital in generating heterogeneity in growth processes across U.S. counties by estimating growth regressions, using the novel semiparametric smooth coefficient quantile regression method in which parameters are unspecified functions of a measure of social capital. The results indicate substantial differences across the quantiles of economic growth in the profile shapes of the coefficient estimates over the level of social capital. Moreover, the coefficient function estimates are highly nonlinear over the level of social capital, providing evidence that the growth process that links initial income, education attainment, ethnic diversity, inequality, population density, and government activity to growth varies with social capital in a nonlinear way.     

Democracy comes to Europe: Franchise extension and fiscal outcomes 1830-1938

This paper examines the relation between public spending and the spread of democracy in Western Europe during the period 1830-1938. Our data set includes measures of the size of the electorate, the election rule, and electoral participation, as well as measures of the size and composition of central government expenditures for 12 countries. We estimate panel regressions, and find that (1) the gradual lifting of socio-economic restrictions on the voting franchise contributed to growth in government spending mainly by increasing spending on infrastructure and internal security; (2) the female suffrage had a weak positive effect, through spending on health, education and welfare; (3) the change from majority to proportional rule, which took place in 10 of the countries, did not contribute to growth in government spending, and held back spending on health, education and welfare; (4) there exists (weak) complementarity between economic development and the spread of democracy.     

On the power of bootstrap tests for stationarity: a Monte Carlo comparison

This paper studies the behavior of recently proposed bootstrap tests for the null hypothesis of stationarity when the data are generated under the alternative hypothesis of a unit root. Using Monte Carlo experiments and empirical examples, it is shown that the power of these tests critically depends on the type of bootstrap employed. Specifically, while tests based on the stationary bootstrap have power functions that are increasing with respect to sample size, those based on the sieve bootstrap have non-monotonic power functions. We argue that this difference arises from the fact that the latter procedure does not impose the null hypothesis when generating the bootstrap samples while the former ensures that the bootstrap samples are stationary, conditional on the original data. Our results therefore suggest that while both forms of bootstrap are effective at providing improved distributional approximations under the null hypothesis, it is important to pay careful attention to the particular type of bootstrap being employed when attempting to distinguish between the unit root and stationarity hypotheses as the choice of bootstrap can have crucial implications for the power of the resulting tests.     

Examining the relationship between municipal consolidation and cost reduction: an instrumental variable approach

This study explores the cost-reduction effects of local government consolidation, using data from Japanese municipalities. We use municipal panel data from Japan for the years 2000, 2005 and 2010, a data set including numerous consolidation cases. Reverse causality between consolidation decisions and size of municipal expenditure is a concern in the voluntary consolidation of local governments. An instrumental variable (IV) methodology is employed to deal with possible endogeneity associated with consolidation decisions. The main finding is that municipal current expenditure per capita increases immediately after consolidation, but then gradually declines. Because consolidation seems to increase per capita expenditure in the absence of the effect of this long-term declining trend, incorporating this trend into estimation is crucial in cost-efficiency analysis of consolidation. It is also shown that conventional panel data regressions yield biased consolidation effects, suggesting the superiority of the IV approach.     

On statistical inference for inequality measures calculated from complex survey data

We examine inference for Generalized Entropy and Atkinson inequality measures with complex survey data, using Wald statistics with variance?Ccovariance matrices estimated from a linearization approximation method. Testing the equality of two or more inequality measures, including sub-group decomposition indices and group shares, are covered. We illustrate with Indian data from three surveys, examining pre-school children??s height, an anthropometric measure that can indicate long-term malnutrition. Sampling involved an urban/rural stratification with clustering before selection of households. We compare the linearization complex survey outcomes with those from an incorrect independently and identically distributed (iid) assumption and a bootstrap that accounts for the survey design. For our samples, the results from the easy to implement linearization method and the more computationally burdensome bootstrap are typically quite similar. This finding is of interest to applied researchers, as bootstrapping is currently the method that is most commonly used for undertaking statistical inference in this literature.     

Government size,government debt and globalization

This article empirically investigates the effect of globalization on government size and debt. Using panel heterogeneous cointegration techniques to a panel of developing and developed countries, it finds that globalization reduces government size and debt. In terms of components of globalization, government size is found to increase with trade openness but decreases with financial, social and political globalization. On the other hand, government debt increases with financial and trade openness but decreases with social and political globalization. The evidence is robust to different estimation methods and different samples. Our data also indicate unidirectional causality running from globalization measures to government size and debt.     

On the median regression for SURE models with applications to 3-generation immigrants data in Sweden

In this paper we generalize the median regression method to be applicable to system of regression equations, in particular SURE models. Giving the existence of proper system wise medians of the residuals from different equations, we apply the weighted median regression with the weights obtained from the covariance matrix of the equations obtained from ordinary SURE method. The benefit of this model in our case is that the SURE estimators utilise the information present in the cross regression (or equations) error correlation and hence more efficient than other estimation methods like the OLS method. The Seemingly Unrelated Median Regression Equations (SUMRE) models produce results that are more robust than the usual SURE or single equations OLS estimation when the distributions of the dependent variables are not normally distributed or the data are associated with outliers. Moreover, the results are also more efficient than is the cases of single equations median regressions when the residuals from the different equations are correlated. A theorem is derived and indicates that even if there is no statistically significant correlation between the equations, using SUMRE model instead of SURE models will not damage the estimation of parameters.     

The size of public employment: An empirical study

Previous empirical studies of government have focused primarily on aggregate financial measures of size. This analysis examines a different measure: the share of public employment in total employment. In empirical tests on OECD countries for 1970 and 1980, the level of public employment is shown to be a clear reflection of voter demand for public goods, electoral support for socialist parties, and political response to the problems of unemployment. In contrast, variables that measure characteristics of the political process, such as degree of government decentralization, strength of interest groups, and voter participation in elections, are not statistically significant.     

Government size,democracy, and corruption: An empirical investigation

Previous studies on the effect of government size on corruption have produced mixed results. In an attempt to explain these ambiguous results, this study investigates the effect of government size on corruption by taking into account the role of the democracy in each country. Using annual data of 82 countries between 1995 and 2008, the estimation results indicate that an increase in government size can lead to a decrease in corruption if the democracy level is sufficiently high and, in contrast, can lead to an increase in corruption if it is too low. As robustness checks, the estimations using a different index of corruption and a different proxy for government size are also conducted. The results reveal that our main findings are robust. Furthermore, to address endogeneity problems, we conduct the instrumental variables estimation and the system generalized method of moments estimation, the results of which also support our primary findings. These results provide some important implications for policymakers seeking to perform government interventions without aggravating corruption.     

Can patent family size and composition signal patent value?

Recent research has proposed a method of patent valuation based on weighting patent family size by the market size of the countries in the family. The premise is that inventors tend to seek greater international coverage for their more valuable patents. The paper presents a novel way to test the ability of market size-weighted patent families to predict patent value and compares the method against extant measures of patent valuation based on patent citations and renewal behaviour. We use forecasting techniques to show that the weighted patent family size measure outperforms other methods in terms of predicting patent life and the number of citations. An advantage of the weighted patent family size measure is that it is based on ex-ante information and is easy to construct for purposes of evaluating patent value. We demonstrate this advantage using a large, comprehensive database of international patent families.     

Testing causality among five fertilizer prices

This article identifies the causal relationships among the prices of five fertilizers using both asymptotic Wald test and resampling (bootstrap) techniques. Monthly data for urea, muriate of potash, rock phosphate, diammonium phosphate and triple super phosphate between 2008 (March) and 2016 (March) are used for the analysis. Results show that the urea price Granger causes all other fertilizer prices. The results of the study are significant in understanding the price dynamics and identify the reference fertilizer price that is useful for the fertilizer industry, farmers and government.     

The efficiency of immunization of infants by local government

The paper makes use of data envelopment analysis (DEA) to measure the cost and production efficiency of local government programmemes for childhood immunization in urban and rural settings in Australia. Model specification is tested for validity, methods are used for ranking efficient units and advanced statistical methods are used to establish confidence intervals around the efficiency estimates. Given the small data set, the cost and production models are valid, and it is concluded that while neither urban nor rural programmes are particularly efficient, there is more room for improvement in rural programmes. Ways of changing methods of delivery are suggested which may increase efficiency.     

Literature analysis of the evaluation of public training programmes in the USA,Europe and China: Implications for the evaluation of farmer training programmes in China

This review aims to inform the evaluation of Chinese farmer training programmes through comparison with studies assessing public training programmes in the USA and Europe. The results of comparative analysis from 62 studies in the USA, Europe and Mainland China suggest that evaluation studies of the farmer training programme should measure the effectiveness of farmer training on agricultural income. Considering the cost and availability of data, cross‐section estimation may be an effective way to evaluate the effectiveness of farmer training programmes in China, but on the basis of controlling the initial demographic characteristics of samples. In particular, political status (whether a party member of Communist Party of China or not), position (whether village cadre or not) and region of residence are considered to be important determinants that impact the effectiveness of farmer training programmes in China. This review sets out directions for the future study of Chinese training programmes, with particular emphasis given to the need for research into the causal effects of different training courses, the dynamic effects arising from variation in the duration of training, and the medium‐run or long‐run effects of training programmes.