Credit growth,current account and financial depth

Exploring the determinants and dynamics of the current account balance is one of the priorities of academic literature and policy circles. Although the effects of structural variables are deeply analysed, a lesser attention has been paid to the impact of financial variables. Drawing on standard empirical current account models and with a large sample of industrial and developing countries, we report a significant deterioration in the current account balance in case of an increase in the credit growth. Moreover, we find that this link is substantially stronger for the developing ones motivating a closer examination. Therefore, we further advance our analysis and show that credit growth causes a stronger impact on the current account balance for lower levels of financial depth. In other words, at the early stages of financial development, acceleration in the credit growth might cause a larger deterioration in the current account balance; thus, it might be suggested that monetary policy and macro-prudential measures aimed at preventing financial excess might be more effective to reduce the external imbalances at the early stages of financial deepening.     

Information Technology As A Factor Of Production: The Role Of Differences Among Firms

Despite evidence that information technology (IT) has recently become a productive investment for a large cross-section of firms, a number of questions remain. Some of these issues can be addressed by extending the basic production function approach that was applied in earlier work. Specifically, in this short paper we: 1) control for individual firm differences in productivity by employing a ‘firm effects’ specification, 2) consider the more flexible translog specification instead of only the Cobb-Douglas specification, and 3) allow all parameters to vary between various subsectors of the economy.

We find that while ‘firm effects’ may account for as much as half of the productivity benefits imputed to IT in earlier studies, the elasticity of IT remains positive and statistically significant. We also find that the estimates of IT elasticity and marginal product are little-changed when the less restrictive translog production function is employed. Finally, we find only limited evidence of differences in IT's marginal product between manufacturing and services and between the ‘measurable’ and ‘unmeasurable’ sectors of the economy. Surprisingly, we find that the marginal product of IT is at least as high in firms that did not grow during 1988–1992 sample period as it is in firms that grew.     

Model uncertainty and asset return predictability: an application of Bayesian model averaging

We investigate model uncertainty associated with predictive regressions employed in asset return forecasting research. We use simple combination and Bayesian model averaging (BMA) techniques to compare the performance of these forecasting approaches in short-vs. long-run horizons of S&P500 monthly excess returns. Simple averaging involves an equally-weighted averaging of the forecasts from alternative combinations of factors used in the predictive regressions, whereas BMA involves computing the predictive probability that each model is the true model and uses these predictive probabilities as weights in combing the forecasts from different models. From a given set of multiple factors, we evaluate all possible pricing models to the extent, which they describe the data as dictated by the posterior model probabilities. We find that, while simple averaging compares quite favorably to forecasts derived from a random walk model with drift (using a 10-year out-of-sample iterative period), BMA outperforms simple averaging in longer compared to shorter forecast horizons. Moreover, we find further evidence of the latter when the predictive Bayesian model includes shorter, rather than longer lags of the predictive factors. An interesting outcome of this study tends to illustrate the power of BMA in suppressing model uncertainty through model as well as parameter shrinkage, especially when applied to longer predictive horizons.     

Interest rate reforms,financial deepening and economic growth in Tanzania: a dynamic linkage

In this paper we examine the dynamic relationship between interest rate reforms and economic growth in Tanzania using two tests. In the first test, we examine the impact of interest rate reforms on financial deepening using a financial deepening model. In the second test, we examine whether the financial deepening, which results from interest rate reforms, Granger‐causes economic growth – using a trivariate model. The empirical findings of our results reveal that there is a significant positive relationship between interest rate reforms and economic growth in Tanzania. However, the results fail to find any support for finance‐led growth.     

Corrigendum to “Characterization of the asymptotic distribution of semiparametric M-estimators” [J. Econometrics 159 (2) (2010) 252–266]

This note provides correction to Ichimura and Lee (2010).     

Nonparametric fixed effects model for panel data with locally stationary regressors

We develop methods for inference in nonparametric time-varying fixed effects panel data models that allow for locally stationary regressors and for the time series length $T$ and cross-section size $N$ both being large. We first develop a pooled nonparametric profile least squares dummy variable approach to estimate the nonparametric function, and establish the optimal convergence rate and asymptotic normality of the resultant estimator. We then propose a test statistic to check whether the bivariate nonparametric function is time-varying or the time effect is separable, and derive the asymptotic distribution of the proposed test statistic. We present several simulated examples and two real data analyses to illustrate the finite sample performance of the proposed methods.     

Simplified Jackknife Variance Estimates for Fuzzy Measures of Multidimensional Poverty

In this paper, we present a practical methodology for variance estimation for multi‐dimensional measures of poverty and deprivation of households and individuals, derived from sample surveys with complex designs and fairly large sample sizes. The measures considered are based on fuzzy representation of individuals' propensity to deprivation in monetary and diverse non‐monetary dimensions. We believe this to be the first original contribution for estimating standard errors for such fuzzy poverty measures. The second objective is to describe and numerically illustrate computational procedures and difficulties in producing reliable and robust estimates of sampling error for such complex statistics. We attempt to identify some of these problems and provide solutions in the context of actual situations. A detailed application based on European Union Statistics on Income and Living Conditions data for 19 NUTS2 regions in Spain is provided.     

基于“家电以旧换新”回收数据评估电子废物产生量估算方法

比较了基于史坦福(Stanford)模型和保有量系数法对我国电子废物产生量的预测,并与中国家电以旧换新活动试点区域的实际回收统计数据进行对比,结果显示除电视机以外,两种估计方法的预测结果都显著高于以旧换新的实际回收数据.其原因首先是产品废弃量的变化深受产品技术变化影响,平板显示技术的快速普及导致CRT电视机废弃量出现短期激增,成为“家电以旧换新”实际回收品的主体,而洗衣机、电冰箱等传统大家电的产品实际使用寿命相对较长;其次是废旧产品回收面临非正式回收部门的竞争,以旧换新以较高的政府补贴引导一定数量的废弃产品流向正规处理企业,但还有相当数量的废旧产品流入了非正式的翻新加工和二手销售渠道.特别是空调和电脑,家庭消费占总消费量的比重较小,产品废弃后的材料回收价值和翻新维修价值都较高,补贴对提升回收量的影响相对较小;最后不同区域之间,预测结果与实际回收情况对比也存在明显的差别.考虑到家电以旧挟新政策停止以后,新颁布实施的废弃电器电子产品回收处理基金的补助力度大幅下降,有资质的回收处理企业重新陷入发展困境.有必要遵循生产者责任延伸制度的原则,积极鼓励扩大生产者的参与,从产品设计和废弃产品回收的逆向物流两方面提高回收利用系统的效率.同时,合理规划再生处理设施的区位和处理规模,需要根据区域和产品特点,对现有预测方法进行优化调整.     

Recovering Hicksian Consumer Surplus within a Collective Model: Hausman's Method for the Household

The purpose of this paper is to describe the implications of the collective model of household behavior for the methods used to estimate the economic value of non-marketed environmental resources. After demonstrating how the separability restrictions inherent in the collective model allow individual preference and household income allocation choices to be distinguished, the paper demonstrates how the framework can be used to recover Hicksian consumer surplus. An algebraic example is used to illustrate how the framework can be used in valuing environmental resources.