Nonresponse in dynamic panel data models

To verify whether data are missing at random (MAR) we need to observe the missing data. There are only two exceptions: when the relationship between the probability of responding and the missing variables is either imposed by introducing untestable assumptions or recovered using additional data sources. In this paper, we briefly review the estimation and test procedures for selectivity in panel data. Furthermore, by extending the MAR definition from a static setting to the case of dynamic panel data models, we prove that some tests for selectivity are not verifying the MAR condition.     

Chaos and sector-specific externalities

Benhabib and Farmer [1996. Indeterminacy and sector specific externalities. Journal of Monetary Economics 37, 397–419] explore the possibility of local indeterminacy in a two-sector model with sector-specific externalities. They find that very small sector-specific externalities are sufficient for local indeterminacy. In this case, it is possible to construct sunspot equilibria where extrinsic uncertainty matters. In this paper, I provide a global analysis of their model revealing the existence of Euler equation branching. This branching allows for regime switching equilibria with cycles and chaotic behavior. These equilibria occur whether the “local dynamics” are determinate or indeterminate.     

City size and urban labor productivity in China: New evidence from spatial city-level panel data analysis

The previous literature has generally found that most Chinese cities were undersized in the 1990s. However, little is known about how urban agglomeration in China has evolved since the country began to experience much faster urbanization and deep marketization after 2000. Based on panel data of 281 cities between 2000 and 2013, our spatial panel data regression results show that the scale impact of city size on urban productivity appears to have an inverted U shape, and its effect will grow when the cities’ industrial structure becomes more dominated by the service sector. There are also significant spatial interactions and spatial heterogeneity of urban agglomeration among Chinese cities. Furthermore, we compute the optimal size for each city and find that most Chinese cities are still undersized in recent years. Based on our findings, we argue that the Chinese government should focus on promoting sufficient growth of medium sized cities in its new urbanization strategy.     

Externalities in the matching of workers and firms in Britain

We provide empirical evidence on the nature of spatial externalities in a matching model for Britain. We use a monthly panel of outflows, unemployment and vacancy stocks data from the registers at Jobcentres in Britain; these are mapped onto travel-to-work areas. We find evidence of significant spill-over effects that are generally in line with the predictions of theory. For example, we find that conditional on local labour market conditions, high unemployment levels in neighbouring areas raise the number of local filled vacancies but lower the local outflow from unemployment.     

中国新型城镇化进程中的金融支持影响研究

通过测度2004~2013年新型城镇化7个相关指标,将因子分析法、主成分分析法结合,对新型城镇化指标进行空间自相关检验,建立新型城镇化水平的综合评价体系。采用空间面板模型,从金融规模、金融效率、金融结构3个方面设定指标来测度中国2004~2013年31个省份金融因素对新型城镇化建设的影响。结果表明,中国城镇化水平整体提高的同时区域差距进一步加大,金融支持是影响新型城镇化水平的重要因素。在未来发展中,应通过加大金融机构对城镇化建设中基础设施的投入,增加城乡一体化产业融合资金支持,改善金融机构对城镇化的服务水平等途径,实现中国新型城镇化水平的提高和可持续发展。     

Modeling monetary policy as an unobserved variable

This paper presents a model of the U.S. Monetary Authority. It is assumed that monetary policy is a single dimensioned unobserved variable that links changes in a set of ‘causal’ variables representing economic goals and changes in money market ‘indicator’ variables. Several issues are examined pertaining to the weights attached to the causal variables including: the lag structure, changes over time, and asymmetric effects of positive and negative changes. As a by product of the model, the paper presents an estimated index of monetary policy for the years 1955–1975.     

Testing a linear dynamic panel data model against nonlinear alternatives

The most popular econometric models in the panel data literature are the class of linear panel data models with unobserved individual- and/or time-specific effects. The consistency of parameter estimators and the validity of their economic interpretations as marginal effects depend crucially on the correct functional form specification of the linear panel data model. In this paper, a new class of residual-based tests is proposed for checking the validity of dynamic panel data models with both large cross-sectional units and time series dimensions. The individual and time effects can be fixed or random, and panel data can be balanced or unbalanced. The tests can detect a wide range of model misspecifications in the conditional mean of a dynamic panel data model, including functional form and lag misspecification. They check a large number of lags so that they can capture misspecification at any lag order asymptotically. No common alternative is assumed, thus allowing for heterogeneity in the degrees and directions of functional form misspecification across individuals. Thanks to the use of panel data with large $N$ and $T$, the proposed nonparametric tests have an asymptotic normal distribution under the null hypothesis without requiring the smoothing parameters to grow with the sample sizes. This suggests better nonparametric asymptotic approximation for the panel data than for time series or cross sectional data. This is confirmed in a simulation study. We apply the new tests to test linear specification of cross-country growth equations and found significant nonlinearities in mean for OECD countries’ growth equation for annual and quintannual panel data.     

Entrepreneurship and market size. The case of young college graduates in Italy

We analyse empirically the effects of urbanization on Italian college graduates' work possibilities as entrepreneurs three years after graduation. We find that doubling the province of work's population density reduces the chances of being an entrepreneur by 2–3 percentage points. This result holds after controlling for regional fixed effects and is robust to instrumenting urbanization. Provinces' competition, urban amenities and dis-amenities, cost of labour, earning differentials between employees and self-employed workers, unemployment rates and value added per capita account for more than half of the negative urbanization penalty. Our result cannot be entirely explained by the presence of negative differentials in returns to entrepreneurship between the most and the least densely populated areas. In fact, as long as they succeed in entering the most densely populated markets, young entrepreneurs are able to reap-off the benefits of urbanization externalities: the elasticity of entrepreneurs' net monthly earnings with respect to population density is 0.02–0.03.     

城市化对碳排放量及强度的影响

基于1995-2009年中国各省的面板数据,利用STIRPAT模型建立了基本的分析框架。首先以全国各省整体为研究对象,研究了城市化对中国碳排放的整体作用方向,然后利用面板变系数模型和门槛面板模型分析了城市化对碳排放的影响的差异。结果表明:整体而言,中国的城市化对碳排放量和碳排放强度均具有正向的影响,且城市化对碳排放强度的影响比对碳排放量的影响大;就不同省份而言,城市化对碳排放的影响存在差异;人口规模、收入水平、产业结构以及城市化水平的变化,均会使城市化与碳排放的关系发生变化,且相对而言,人口规模和城市化水平对城市化与碳排放的关系影响更大。     

Scale Externalities in Korea

This paper estimates the nature and magnitude of scale externalities in a developing country, Korea, in the period 1983–1993. This is a period of rapid industry deconcentration from Seoul to other metro areas, providing a context where externalities are measured when local scale magnitudes are changing dramatically. The data allow us to examine the emerging degree of national industrial concentration in different industries, as related to their scale externality magnitudes. We also examine whether individual industries agglomerate in cities which have a comparative advantage for that industry.     

我国省(区)人口城镇化水平与速度的类型特征及影响因素

在分析1990年以来我国各省(区)人口城镇化水平和城镇化速度差异的基础上,按城镇化进程特征将各省(区)划分为四种类型.并采用面板数据分析1990年-2005年各类型省(区)的城镇化影响因素及其差异.分析结果表明:各影响因素对不同类型省(区)的影响作用程度不同;经济发展水平和非农就业比重对各类省(区)城镇化水平都有显著影响;对外贸易规模仅对城镇化水平高的两类省(区)的城镇化影响显著,但是推动作用比较小;教育水平对城镇化水平较低的两类省(区)城镇化进程的推动作用显著.     

Missing Data: A Unified Taxonomy Guided by Conditional Independence

Recent work (Seaman et al., 2013 ; Mealli & Rubin, 2015 ) attempts to clarify the not always well‐understood difference between realised and everywhere definitions of missing at random (MAR) and missing completely at random. Another branch of the literature (Mohan et al., 2013 ; Pearl & Mohan, 2013 ) exploits always‐observed covariates to give variable‐based definitions of MAR and missing completely at random. In this paper, we develop a unified taxonomy encompassing all approaches. In this taxonomy, the new concept of ‘complementary MAR’ is introduced, and its relationship with the concept of data observed at random is discussed. All relationships among these definitions are analysed and represented graphically. Conditional independence, both at the random variable and at the event level, is the formal language we adopt to connect all these definitions. Our paper covers both the univariate and the multivariate case, where attention is paid to monotone missingness and to the concept of sequential MAR. Specifically, for monotone missingness, we propose a sequential MAR definition that might be more appropriate than both everywhere and variable‐based MAR to model dropout in certain contexts.     

城市化与能源消耗间关系实证研究

通过利用2000—2009年我国的省级面板数据,建立时间和空间双固定效应的面板空间杜宾模型,发现我国存在一条U形的城市化能耗库兹涅茨曲线,该曲线的转折点出现在城市化率约为24%的阶段。现阶段我国的城市化水平已经处在该曲线的右侧部分,表明如果我国的城市化率在今后仍不断提高的话,由城市化所导致的能耗将迅速增长。同时还发现城市化在我国能耗增长中的贡献比重较大,但对于在2003年出现的我国能耗迅速增加的拐点,从城市化的角度找不到解释。最后提出如果今后我国城市化率进一步提高,由能耗迅速增加所导致的城市发展的离心力达到一定程度,将会对我国的城市化格局产生重要的影响。     

空间加权矩阵设置与空间面板参数估计效率

总结了常用的空间加权矩阵的一般构建方法和研究领域内新提出的空间加权矩阵的构建方法,从宏观与微观层面,量化分析了空间加权矩阵设置对于空间面板参数估计效率、空间效应识别的影响效应。结论表明：宏观数据层面,随着空间加权矩阵复杂程度的提高,无论是空间面板固定效应模型还是空间面板随机效应模型,参数估计的有效性与一致性都显著提高并且广义矩参数估计方法优于拟极大似然估计方法,复合的空间加权矩阵条件下,拉格朗日乘子检验方法的功效更高;微观数据层面,回归结果表明四种不同类型的空间加权矩阵的设置,对于聚集外部性引致的企业全要素生产率增长的空间边界的识别具有显著影响,复合的空间加权矩阵更有效。     

Hedonic Housing Prices in Paris: An Unbalanced Spatial Lag Pseudo‐Panel Model with Nested Random Effects

This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990–2003. This is done using maximum likelihood estimation, taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four quartiers (quarters), which in turn contain between 15 and 169 blocks (îlot, in French) per quartier. This is an unbalanced pseudo?panel data containing 156,896 transactions. Despite the richness of the data, many neighborhood characteristics are not observed, and we attempt to capture these neighborhood spillover effects using a spatial lag model. Using likelihood ratio tests, we find significant spatial lag effects as well as significant nested random error effects. The empirical results show that the hedonic housing estimates and the corresponding marginal effects are affected by taking into account the nested aspects of the Paris housing data as well as the spatial neighborhood effects.Copyright © 2014 John Wiley & Sons, Ltd.     

中国城市化滞后根源新论

目前 ,很多人认为城乡户籍制度、重工业化战略和城市建设不力是中国城市化滞后的主要原因。实际上 ,这只是中国城市化滞后的现象和结果 ,其根源在于推动中国城市化进程的根本动力———工业结构处于世界产业体系中下游 ,城市化进程缺乏强大的经济基础 ;城镇流动人口经济收入较低 ,不能跨越城市化最低门槛 ,完成城市化的彻底转变 ;作为城镇人口就业的主要渠道———服务业———达不到人口城市化起跑的经济、人口的临界点。这三点决定了中国城市化滞后现象必将长期存在 ,而合理加速城市化进程的重点是确定有希望城市化的流动人口阶层 ,让这部分人口先城市化     

Income convergence within the MENA countries: A panel unit root approach

This article aims at testing the convergence hypothesis in MENA region using new tests of a unit root in panel data. Evans and Karras [Evans P., & Karras G. (1996). Convergence revisited. Journal of Monetary Economics, 37, 249–265] and Bernard and Jones [Bernard A., & Jones C. I. (1996). Productivity across industries and countries: Time series theory and evidence. The Review of Economics and Statistics, 135–146] recommend this technique to evaluate the income convergence hypothesis. According to them it avoids econometric problems of the cross-countries growth regressions testing convergence and sample bias of the multivariate cointegration techniques. We test for both absolute and the conditional convergence with panel unit root tests using the Summers and Heston's data 5.6 and 6.1 on the periods of 1960 to 1990 and from 1960 to 2000. The absolute convergence hypothesis use panel unit roots test with no fixed individual effects. The catching-up hypothesis is not rejected for most groups of countries of the region during both periods. If we allow a break in the unit root tests, the hypothesis is not rejected for more groups. The conditional convergence requires panel unit root tests with fixed individual effects. Again, during the whole periods, the conditional convergence is not rejected for the major part of the remaining groups of MENA countries.     

Influence measurement of rapid urbanization on agricultural production factors based on provincial panel data

The proportion of agricultural output value is continuously decreasing because of the process of rapid urbanization, but it is still the basis of economic development and urban construction. Agricultural production factors are at the core of agriculture, and have an important influence on the agricultural output value. In the period of rapid urbanization, high technical and capital investment improved agricultural production efficiency and increased the income of farmers. However, in recent years it also introduced serious problems for agricultural production, including aging farmers and weakening labor markets, farmland conversion, and soil pollution. In this study, we estimated the elasticity coefficients of agricultural production factors, including labor, capital and technique, using the improved Cobb–Douglas production function and provincial panel data from 2000 to 2015, and measured the effects of urbanization on elasticity coefficients using the Euclidean metric and gravity model. The results were as follows. (1) In time, the elasticity coefficient of labor was stable, and with a low increase from 0.238 to 0.304. However, the elasticity coefficients of land and capital had been increasing since 2000, by 1.125 and 0.140, respectively. The higher elasticity coefficient of agricultural production factors was gradual from labor to capital, with the growth of urbanization level. (2) In space, the elasticity coefficients were the space distribution, as urbanization divided into east, central and west: the elasticity coefficients of labor and land in the eastern regions were higher, and the elasticity coefficient of capital in the central regions was higher. (3) Economic urbanization had a larger positive influence on the elasticity coefficient of capital, and the population had a larger negative influence on elasticity coefficients of labor. The quantitative results were similar to the development status, but there were different influences on elasticity coefficients in different provinces. (4) Finally, the study put forward suggestions for agricultural sustainable development according to the function mechanism of urbanization on agricultural production factors, including increasing the attention paid agriculture, ensuring a stable market environment, and optimizing the industrial structure, with reference to scientific, green and healthy agriculture.     

The lag relationship between wholesale and consumer prices: An application of the Hatanaka-Wallace procedure

This paper examines the lag distribution relating wholesale to consumer price changes. Sims' causality test indicates a one-sided lag structure. Following Hatanaka and Wallace, parameters of the lag distribution which can be estimated with relatively high precision are emphasized. Thus, our concern is with the sum of coefficients and the first four moments of the distribution. Short-run effects are estimated from lag moments using Pearson's method for equating moments. As a smoothness prior, a Beta distribution in the lag weights is suggested. Tests for bias due to missing components in the wholesale price index indicate little is lost because of misspecification.     

中国城镇化进程对房地产价格影响的实证分析

使用城镇化率、流动人口占比、城镇居民人均总收入和房屋竣工面积4个变量指标来反映我国城镇化进程,运用随机效应面板数据模型,对比分析2005—2013年全国、较发达省份和发展中省份的城镇化进程对房地产价格的影响。实证研究表明：城镇化率提高、流动人口占比增加,对房价的影响实际非常有限;城镇居民人均总收入水平的增加才是引起房价上涨的最重要因素;房屋竣工面积的扩大则引起房价的下跌。区域对比研究还发现,由于城镇化进程不同,相比较发达省份,发展中省份的外来务工人员产生了更有效的住房需求。