Instrumental variable estimation of a spatial autoregressive panel model with random effects

This paper extends the instrumental variable estimators of Kelejian and Prucha (1998) and Lee (2003) proposed for the cross-sectional spatial autoregressive model to the random effects spatial autoregressive panel data model. It also suggests an extension of the Baltagi (1981) error component 2SLS estimator to this spatial panel model.     

A simple spatial dependence test robust to local and distributional misspecifications

In this paper, we derive a class of modified score tests robust to local and distributional misspecifications for testing spatial error autocorrelation and spatial lag dependence. The proposed tests are general enough to include several popular tests for the spatial dependence as special cases. Moreover, we show that the popular test statistics proposed by Burridge (1980) and Anselin et al. (1996) are robust to distributional misspecification although they are derived under normality assumption.     

Income convergence in Japan: A Bayesian spatial Durbin model approach

With the collapse of the bubble economy in the early 1990s, economic disparities among both people and regions have arisen in Japan. Although developments in spatial econometrics have provided regional convergence studies with highly effective tools to explicitly consider spatial dependence and heterogeneity, there has as yet been no significant research on Japan's economic disparity using spatial econometrics. Moreover, most conventional regional convergence studies on Japan study the post-war high economic growth period before the economic bubble.Hence, the objective of this study is to analyze regional income disparities in Japan in the period after the bubble burst. We use the Bayesian spatial Durbin model, which can consider both spatial dependence and heterogeneity. The data used in this research are annual data collected at the municipality level during 1989-2007. To the best of our knowledge, no research has been conducted to analyze Japan's regional income disparities at the municipality level, though some research has been done at the prefecture level.First, the study suggests that σ-convergence does not hold whether or not spatial dependence is considered. Second, it analyzes regional income convergence by applying the simplified Bayesian spatial Durbin model to the β -convergence approach. The results show that β-convergence holds over 1990-2007.     

Hierarchically spatial autoregressive and moving average error model

This paper considers a hierarchically spatial autoregressive and moving average error (HSEARMA) model. This model captures the spatially autoregressive and moving average error correlation, the county-level random effects, and the district-level random effects nested within each county. We propose optimal generalized method of moments (GMM) estimators for the spatial error correlation coefficient and the error components' variances terms, as well as a feasible generalized least squares (FGLS) estimator for the regression parameter vector. Further, we prove consistency of the GMM estimator and establish the asymptotic distribution of the FGLS estimator. A finite-scale Monte Carlo simulation is conducted to demonstrate the good finite sample performances of our GMM-FGLS estimators.     

Uncertain spatial demand and price flexibility: A state space approach to duopoly

Sufficient conditions for a unique price equilibrium, in terms of the uncertainty distribution and the state contingent consumer distributions, are given for spatial duopoly. Also considered are efficiency and endogenous locations for the symmetric case and comparative statics on price flexibility.     

Institutions and geography: Empirical test of spatial growth models for European regions

This article provides an empirical assessment of the growth experiences of European regions, during the period 1991–2004, by taking into account the spatial effects due to both institutions and geography. These effects have been modelled by means of specific controls and by using a non-conventional spatial weight matrix. Results favour a model dealing with substantive spatial externalities. Within this framework, the country-specific institutions are strongly and positively related to the regional productivity's growth rate. In addition, the geo-institutional proximity increases the spatial dependence of the regional output per worker and raises the speed of convergence. By contrast, the pure geographical metrics is underperforming, while underestimating the convergence dynamics.     

Spatial dynamics and convergence: The spatial AK model

We study the optimal dynamics of an AK economy where population is uniformly distributed along the unit circle. Locations only differ in initial capital endowments. Spatio-temporal capital dynamics are described by a parabolic partial differential equation. The application of the maximum principle leads to necessary but non-sufficient first-order conditions. Thanks to the linearity of the production technology and the special spatial setting considered, the value function of the problem is found explicitly, and the (unique) optimal control is identified in feedback form. Despite constant returns to capital, we prove that the spatio-temporal dynamics, induced by the willingness of the planner to give the same (detrended) consumption over space and time, lead to convergence in the level of capital across locations in the long-run.     

Saving–investment Association and Regional Capital Mobility in China: A Nonparametric Panel Approach

Using a nonparametric panel data model, this paper estimates the degree of time‐varying and province‐specific capital mobility in China during 1970–2006. We estimate the savings–investment association, that is, the savings retention rate à la Feldstein and Horioka, as a measure of capital mobility. We also split the total savings (investment) into private and government savings (investment) to explore the role of government in improving capital mobility. Over time, we find an improvement in capital mobility after the mid‐1990s. Across provinces, we observe higher capital mobility in eastern/coastal regions. From the 1990s, the government is found to play a less important role in promoting capital mobility. Across provinces, the government is found to be more important in either the municipalities (Shanghai and Beijing) or the less developed inland provinces.     

A public firm in a model of spatial duopoly with price discrimination

We visit the role of privatization in the location decision of firms in an industry where no firm can produce all varieties demanded. We demonstrate that the Nash equilibrium locations are socially optimal, in the presence of a publicly owned firm, notwithstanding the degree of privatization.     

Housing price and entrepreneurship in China

Housing price has increased dramatically in China during the past decade. The appreciation of house value could relax credit constraint and thus encourage entrepreneurship. However, a house serves as both an important investment channel and a prerequisite for marriage in China. The continuous high return of investment in housing and intensified marriage market competition make house purchase a priority for young people and their parents, which would crowd out entrepreneurial activities. Using two large datasets, we find that high housing price in general discourages entrepreneurial activities for urban adults. For house owners, while house value appreciation has a positive wealth effect, the ratio of mortgage over income has a negative effect. For non-owners, a higher ratio of housing price over income corresponds to a lower probability of entrepreneurship. This study highlights the negative consequences of surging housing price on entrepreneurship in developing countries.     

DEMOGRAPHIC SHIFT,POPULATION AGEING AND ECONOMIC GROWTH IN CHINA: A COMPUTABLE GENERAL EQUILIBRIUM ANALYSIS

Abstract. Using a computable general equilibrium (CGE) model and a given ageing profile of the population to forecast the growth path of China's economy during the twenty‐first century, this study finds that: population ageing leads to declining economic growth as labour supply shrinks and the rate of physical capital formation declines; households’ material living standards improve, albeit at a declining rate; falling domestic investment partially offsets declining national savings; and the resulting saving‐investment surplus generates a current account surplus and capital outflows. Finally, the main force that can sustain China's economic growth against the backdrop of population ageing is productivity improvement.     

A spatial analysis of provincial corporate income tax responses: evidence from Canada

Abstract.  Using a model of interdependent tax choices, and accounting for equalization entitlements and general transfers, this paper estimates – making use of a spatial econometric framework – corporate income tax-setting functions for all Canadian provincial governments. The results show that there is a statistically significant positive fiscal interaction among a subset of provinces and between all provinces and the federal government. Provincial corporate income taxes are also found to be negatively related to equalization entitlements, general federal transfers, and the federal corporate income tax. A robustness check on the fiscal relationship between Ontario and Quebec verifies the existence of significant bi-directional fiscal interdependencies. The paper also introduces U.S state corporate income taxes as covariates and examines their interaction with Canadian provinces.     

Nonlinear economic growth: Some theory and cross-country evidence

This paper aims to test the existence of different growth regimes, that is of different relationships between growth rate and income level. We propose a simple nonlinear growth model and test its empirical implications by estimating Markov transition matrices and stochastic kernels. We show that growth is indeed nonlinear: a first phase of slow or zero growth is followed by a take-off and, finally, by a phase of deceleration. We discuss the relevance of these results with respect to the issue of convergence and reversibility of development, in the light of models of structural change and technological diffusion.     

What drives housing price dynamics in Greece: New evidence from asymmetric ARDL cointegration

In this paper, we study the dynamics between house prices and selected macroeconomic fundamentals in Greece. The empirical analysis applies the asymmetric ARDL cointegration methodology proposed by Shin, Yu and Greenwood-Nimmo (2011) over the period from January 1999 to May 2011. The evidence suggests that ignoring the intrinsic nonlinearities may lead to misleading inference. In particular, the results reveal significant differences in the response of house prices to positive or negative changes of the explanatory variables in both the long- and short-run time horizons. The obtained evidence of asymmetry could be of major importance for more efficient policymaking and forecasting in the Greek house market.     

Forecasting the US real house price index: Structural and non-structural models with and without fundamentals

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its downturn in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data sets — extracting common factors (principle components) in factor-augmented vector autoregressive or Bayesian factor-augmented vector autoregressive models as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive model. We compare the out-of-sample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). In addition, when we use simple average forecast combinations, the combination forecast using the 10 best atheoretical models produces the minimum RMSEs compared to each of the individual models, followed closely by the combination forecast using the 10 atheoretical models and the DSGE model. Finally, we use each model to forecast the downturn point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a downturn with any accuracy, suggesting that forward-looking microfounded dynamic stochastic general equilibrium models of the housing market may prove crucial in forecasting turning points.     

Stock exchange mergers and return co-movement: A flexible dynamic component correlations model

The creation of a common cross-border stock trading platform is found, by use of a Flexible Dynamic Component Correlations (FDCC) model, to have increased long-run trends in conditional correlations between foreign and domestic stock market returns.     

Search, migration, and urban land use: The case of transportation policies

We develop a search-matching model with rural-urban migration and an explicit land market. Wages, job creation, urban housing prices are endogenous and we characterize the steady-state equilibrium. We then consider three different policies: a transportation policy that improves the public transport system in the city, an entry-cost policy that encourages investment in the city and a restricting-migration policy that imposes some costs on migrants. We show that all these policies can increase urban employment but the transportation policy has much more drastic effects. This is because a decrease in commuting costs has both a direct positive effect on land rents, which discourages migrants to move to the city, and a direct negative effect on urban wages, which reduces job creation and thus migration. When these two effects are combined with search frictions, the interactions between the land and the labor markets have amplifying positive effects on urban employment. Thus, improving the transport infrastructure in cities can increase urban employment despite the induced migration from rural areas.     

Nonlinearities and heterogeneity in environmental quality: An empirical analysis of deforestation

We use a panel data set of 59 developing countries over the 1972–1994 period to study the deforestation process. Relying on both parametric and semiparametric models, we examine nonlinearities and heterogeneity in the deforestation process. We first study the existence of an Environmental Kuznets Curve (EKC) and then analyze determinants of deforestation. Our data sample provides no evidence of an EKC. We also find that political institution failures may worsen the deforestation process in developing countries.     

The effect of monetary policy on real house price growth in South Africa: A factor-augmented vector autoregression (FAVAR) approach

This paper assesses the impact of monetary policy on real house price growth in South Africa using a factor-augmented vector autoregression (FAVAR), estimated using a large data set comprising of 246 quarterly series over the period 1980:01 to 2006:04. The results based on the impulse response functions indicate that, in general, house price inflation responds negatively to monetary policy shock, but the responses are heterogeneous across the middle-, luxury- and affordable-segments of the housing market. The luxury-, large-middle- and medium-middle-segments are found to respond much more than the small-middle- and the affordable-segments of the housing market. More importantly, we find no evidence of the home price puzzle, observed previously by other studies that analyzed house prices using small-scale models. We put this down to the benefit gained from using a large information set.     

Spurious deterministic seasonality and autocorrelation corrections with quarterly data: Further Monte Carlo results

Following recent work of Franses, Hylleberg and Lee (FHL), this paper analyses the consequences of fitting a deterministic seasonal model to a quarterly time series which can be (at least approximately) described by a seasonal unit root(s) model. Besides the distribution of the coefficient of determination, the empirical distributions of two commonly used statistics are also investigated through Monte Carlo experiments for small, moderately large and large samples. FHL's work is also extended allowing the possibility of residual autocorrelation corrections. The main conclusion that emerges from the results is that one should not try to measure the importance of deterministic seasonality nor test for its presence in the context of such (static) regression models, even when using some form of residual autocorrelation correction. A simple empirical application is provided to illustrate our results. First version received: July 1997/final version received: July 1998