Income convergence prospects in Europe: Assessing the role of human capital dynamics

We employ income projection models based on human capital dynamics in order to assess quantitatively the role that educational improvements are expected to play as a driver of future income convergence in Europe. We concentrate on income convergence dynamics between emerging economies in Central and Eastern Europe and Western European countries during the next 50 years. Our results indicate that improvements in human capital contribute significantly to the income convergence potential of European emerging economies. Using realistic scenarios, we quantify the effect that future human capital investment paths are expected to have in terms of speeding up the income convergence process in the region. The income projection exercise shows that the returns to education in terms of income convergence in Europe could be sizeable, although it may take relatively long for the poorer economies of the region to rip the growth benefits.     

Does Evidence on Regional Economic Convergence Depend on the Estimation Strategy? Outcomes from Analysis of a Set of NUTS2 EU Regions

Abstract

The regional economic convergence/divergence issue has been discussed extensively recently, but results obtained are not always interpretable unequivocally as a consequence of the different estimation strategies used. As it is widely recognized, the most common theoretical framework applied to measure the speed of economic convergence among countries or regions remains the β-convergence approach, linked to the neoclassical Solow model. There have been many attempts to consider variations of the basic cross-sectional specification ranging from panel data models to Bayesian spatial econometric techniques. The application of spatial econometric methodologies is an essential tool for proper statistical inference on regional data. In this context, the aim of this paper is to connect the different results obtained in the literature. More specifically, we address whether or not evidence on convergence depends upon the estimation strategy, by taking the same set of data and systematically comparing the results obtained from different estimation strategies. The results from a set of NUTS2 EU regions conclude that both the model implied by the cross-sectional analysis and the one referring to the space-time dynamics incorporated in the panel specification point to convergence. The concept of convergence implied is, however, quite different, as demonstrated throughout the paper.     

Divergent regional development, factor mobility, and nontraded goods

Using an endogenous growth model with learning-by-doing effects in the production of a traded good, we derive divergent regional-growth paths in a two-region-three-good setting. A nontraded-goods sector using a mobile as well as an immobile factor of production provides the possibility of a steady-state equilibrium with a dispersed distribution of mobile workers. The paper investigates regional specialization, trade, and migration patterns in the steady-state equilibrium as well as in the transition process towards the steady-state. The long-run production and trade patterns of the regions are determined by history-dependent processes.     

中国不同区域物流发展与经济增长的比较研究

目前东部地区,物流发展是经济增长的重要原因,而经济增长也对物流发展产生很大影响;而在中部和西部,经济增长对物流发展具有促进作用,但物流对经济增长的反作用并不显著.因此,提高中西部物流的现代化水平和物流管理技术将是中国未来中西部物流发展的关键所在.     

城市居民财产性收入与贫富差距的实证分析

利用1988～2009年国家统计局全国入户调查数据,本文研究了我国城市居民财产性收入的规模、组成、变化以及其对收入差距的贡献。采用基尼系数的分解方法,将每年的收入差距分解到各个收入成分的贡献,并发现与其他收入形式相比,财产性收入分布的基尼系数是最高的,对总收入差距的贡献也在迅速扩大,这一现象值得重视。本文还分别对东、中、西部地区进行了分析,发现财产性收入主要集中在东部地区。     

Green shoots and double dips in the euro area: A real time measure

In order to perform real-time business cycle inferences and forecasts of GDP growth rates in the euro area, we use an extension of the Markov-switching dynamic factor models that accounts for the features of the day-to-day monitoring of economic developments, such as ragged edges, mixed frequencies and data revisions. We provide examples that show the nonlinear nature of the relationships between data revisions, point forecasts and forecast uncertainty. Based on our empirical results, we think that the real-time probabilities of recession inferred from the model are an appropriate statistic for capturing what the press call green shoots, and for monitoring double-dip recessions.     

Growth, cycles and convergence in US regional time series

This article reports the results of fitting unobserved components (structural) time series models to data on real income per capita in eight regions of the United States. The aim is to establish stylised facts about cycles and convergence. It appears that while the cycles are highly correlated, the two richest regions have been diverging from the others in recent years. A new model is developed in order to characterise the converging behaviour of the six poorest regions. The model combines convergence components with a common trend and cycles. These convergence components are formulated as a second-order error correction mechanism which allows temporary divergence while imposing eventual convergence. After fitting the model, the implications for forecasting are examined. Finally, the use of unit root tests for testing convergence is critically assessed in the light of the stylised facts obtained from the fitted models.     

Markov-switching dynamic factor models in real time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as mixed sampling frequencies and ragged-edge data. First, we evaluate the theoretical gains of using data that are available promptly for computing probabilities of recession in real time. Second, we show how to estimate the model that deals with unbalanced panels of data and mixed frequencies, and examine the benefits of this extension through several Monte Carlo simulations. Finally, we assess its empirical reliability for the computation of real-time inferences of the US business cycle, and compare it with the alternative method of forecasting the probabilities of recession from balanced panels.     

L‐moments skewness and kurtosis as measures of regional convergence and cohesion

The paper deals with the statistical modeling of convergence and cohesion over time with the use of kurtosis, skewness and L‐moments. Changes in the shape of the distribution related to the spatial allocation of socio‐economic phenomena are considered as an evidence of global shift, divergence or convergence. Cross‐sectional time‐series statistical modeling of variables of interest is to overpass the minors of econometric theoretical models of convergence and cohesion determinants. L‐moments perform much more stable and interpretable than classical measures. Empirical evidence of panel data proves that one pure pattern (global shift, polarization or cohesion) rarely exists and joint analysis is required.     

Capital utilization, economic growth and convergence

Optimal decisions by economic agents regarding the utilization of capital lead to empirically plausible speeds of convergence in one-sector models of economic growth. The relationship between depreciation and capital utilization plays a crucial role in slowing down convergence to the steady state. Cross-country differences in the extent to which the capital utilization decision is internalized along the transition path may lead to differences in convergence rates, even for countries with similar initial and terminal conditions. Finally, by assuming a constant depreciation rate and full capital utilization, standard growth models may be overstating the magnitude of the steady-state equilibrium.     

区域经济一体化经济增长收敛性的实证研究

本文采用δ收敛考察欧盟(欧共体)在1955年-2000年和东盟在1965年-2005年区域经济一体化与经济增长收敛的关系,发现欧盟在1955年-1990年呈现显著的经济增长收敛,而东盟成立后经济增长呈发散趋势。本文通过分析认为,呈现经济增长收敛的区域经济一体化具有如下特点:一是经济一体化成员国消除了彼此间的贸易壁垒,区域内部基本实现自由贸易;二是经济一体化成员国之间的贸易流量成为各自对外贸易的主要流量;三是FDI效应导致成员国之间的资源配置进一步优化。     

Forecasting and explaining aggregate consumer credit delinquency behaviour

We model aggregate delinquency behaviour for consumer credit (including credit card loans and other consumer loans) and for residential real estate loans using data up until 2008. We test for cointegrating relationships and then estimate short run error correction models. We find evidence to support the portfolio explanations of declines in credit quality for consumer and for real estate loans, but support for the reduced stigma explanation was restricted to real estate loans. Evidence supportive of household-level explanations of irrational borrowing and unexpected net income shocks was found for consumer and real estate loans, but evidence of strategic default was restricted to the volume of consumer loans and real estate loans, and not for credit cards. We also found that the error correction model gave forecasts of the volume of delinquent consumer debt which were of an accuracy comparable to that of an ARIMA model.     

Testing Granger Causality in the presence of threshold effects

This paper proposes a Granger Causality test allowing for threshold effects. The proposed test can be conducted on the basis of the threshold autoregressive distributed lag model or the augmented logistic smooth transition autoregressive model. The proposed test is applied to the U.S. civilian unemployment rate, and it is shown that real investment, real GDP and real interest rate are helpful for improving the in-sample fit of unemployment.     

我国居民收入差距成因分析及对策探讨

随着我国国民经济的持续快速发展和收入水平的普遍提高,收入渠道的多元化促进了居民收入格局的多样化,带来了经济利益在不同群体间的重新调整和社会收入差距的加剧.居民收入差距在城乡、行业、地区之间的扩大,已成为阻碍社会经济持续发展的不利因素.因此,深入分析我国居民收入分配状况,寻找相应的对策,逐步缩小居民收入差距,更具迫切性和现实意义.     

Employment Growth in Italian Local Labour Systems: Issues of Model Specification and Sectoral Aggregation

Abstract

In this paper we construct a model to estimate local employment growth in Italian local labour markets for the period 1991–2001. The model is constructed in a similar manner to the original models of Glaeser et al. (1992), Henderson et al. (1995) and Combes (2000). Our objective is to identify the extent to which the results estimated by these types of models are themselves sensitive to the model specification. In order to do this we extend the basic models by successively incorporating new explanatory variables into the model framework. In addition, and for the first time, we also estimate these same models at two different levels of sectoral aggregation, for the same spatial structure. Our results indicate that these models are highly sensitive to sectoral aggregation and classification and our results therefore strongly support the use of highly disaggregated data.     

Onward the Spatial: an Essay on the Nature and Relevance of Regional Economics

Abstract

Regional economics appears to be losing its currency in academic discourse, with a clear preference over recent years for the term ‘spatial economics’. This essay examines the nature of the developments in order to explore their implications for regional economics, focusing on four key aspects: empirical methods and the ‘tools’ of regional economics; theory and the appropriate spatial scale; the ‘regional problem’; and regional policy. It finds reasons to suggest that the ‘region’ is of less importance, but argues that the use of the term ‘spatial’ does not reflect dissatisfaction with regional economics, but rather it signals the reinvigoration of the subject from its formal connection to mainstream economics. This is primarily in the form of the new economic geography model, although limitations with this have led to an unsatisfactory form of regional policy that is based on growth theory.

Avance de l’économie spatiale: une communication sur la nature et la pertinence de l’économie régionale

RÉSUMÉ L’économie régionale semble avoir perdu du terrain dans les discussions académiques, et on lui préfère clairement, depuis quelques années, l'expression ‘économie spatiale’. La présente communication se penche sur la nature des développements, afin d'explorer leurs implications pour l’économie régionale, en examinant les quatre aspects principaux suivants: les méthodes empiriques et les ‘outils’ de l’économie régionale; la théorie et l’échelle spatiale appropriée; le ‘problème régional’; et la politique régionale. Il détermine des raisons pour affirmer que la ‘région’ joue un rôle moins important, mais estime que l'usage du mot ‘spatial’ ne reflète pas le mécontentement avec l’économie régionale, mais indique un renouveau pour ce sujet après ses liens officiels avec l’économie générale. Ce renouveau se présente principalement sous forme du nouveau modèle de géographie économique, bien que certaines de ses limitations risquent de donner lieu à une forme peu satisfaisante de politique régionale, basée sur la théorie de la croissance.

Avance de lo espacial: un trabajo sobre la naturaleza y la importancia de la economía regional

RÉSUMÉN?La economía regional parece estar perdiendo su difusión dentro de la disertación académica, mientras que durante los últimos años se observa una preferencia clara por el término ‘economía espacial’. Este trabajo examina la naturaleza de los desarrollos con objeto de explorar sus implicaciones para la economía regional, centrándose en cuatro aspectos clave: métodos empíricos y las ‘herramientas’ de la economía regional; teoría y la escala espacial apropiada; el ‘problema regional’; y política regional. Encuentra razones que sugieren que la ‘región’ tiene menor importancia, aunque arguye que el uso del término ‘espacial’ no refleja insatisfacción con la economía regional, sino que indica la revitalización del tema con respecto a su conexión formal con la economía dominante. Esto se da principalmente en la forma del nuevo modelo de geografía económica, aunque sus limitaciones pueden resultar en una forma insatisfactoria de política regional basada en teoría de crecimiento.

     

Bayesian Comparison of ARIMA and Stationary ARMA Models

Time series analysts have long been concerned with distinguishing stationary generating processes from processes for which differencing is required to induce stationarity. In practical applications, this issue is addressed almost invariably through formal hypothesis testing. In this paper, we explore some aspects of the Bayesian approach to the problem, leading to the calculation of posterior odds ratios. Interesting features arise in the simplest possible variant of the problem, where a choice has to be made between a random walk and a stationary first order autoregressive model. We discuss in detail the analysis of this case, and also indicate how our approach extends to the more general comparison of an ARIMA model with a stationary competitor.     

Forecasting monthly and quarterly time series using STL decomposition

This paper is a re-examination of the benefits and limitations of decomposition and combination techniques in the area of forecasting, and also a contribution to the field, offering a new forecasting method. The new method is based on the disaggregation of time series components through the STL decomposition procedure, the extrapolation of linear combinations of the disaggregated sub-series, and the reaggregation of the extrapolations to obtain estimates for the global series. Applying the forecasting method to data from the NN3 and M1 Competition series, the results suggest that it can perform well relative to four other standard statistical techniques from the literature, namely the ARIMA, Theta, Holt-Winters’ and Holt’s Damped Trend methods. The relative advantages of the new method are then investigated further relative to a simple combination of the four statistical methods and a Classical Decomposition forecasting method. The strength of the method lies in its ability to predict long lead times with relatively high levels of accuracy, and to perform consistently well for a wide range of time series, irrespective of the characteristics, underlying structure and level of noise of the data.     

Sectoral Shocks and Metropolitan Employment Growth

In this paper, we study the sources of industry employment growth in each of five metropolitan statistical areas (MSAs). The objective is to understand the relative importance of aggregate disturbances versus local sectoral shocks in generating observed employment fluctuations at the MSA level. The empirical evidence presented in this paper derives from structural vector autoregressions (SVARs), estimated for each of the five MSAs. Estimations use monthly employment data covering nine one-digit industrial categories for the period 1951:1–1999:8, as well as two variables that capture the influences of aggregate (i.e., national) shocks on MSAs. We find that within-MSA industry shocks explain considerably more of the forecast error variance in industry employment growth than do aggregate shocks. Sectoral shocks account for between 87 and 94% of the 36-month-ahead forecast error variance. Among individual local sectors, shocks to MSA-specific government, manufacturing, and service sector employment growth are the predominate sources of variability.