我国农村居民收入分配差距新变化

本文利用最新中国家庭收入调查数据,分析2013—2018年我国农村居民收入分配的新状况,使用无条件分位数回归方法,讨论农村收入差距变化的主要原因。研究发现,2013—2018年我国农村居民收入显著增长,农村内部收入差距呈现一定的扩大趋势。市场化收入贡献率下降是农村内部差距上升的主要原因,低收入群体市场化收入增速下降、高收入群体要素回报率上升,导致这一时期农村收入差距有所扩大。本文建议加大政策扶持力度,稳定农产品市场价格,促进低收入群体收入稳定增长。要充分发挥农村高收入群体的作用,带动低收入农民致富增收,并有效缩小农村收入差距。     

Does Shariah compliance make interest rate sensitivity of Islamic equities lower? An industry level analysis under different market states

This paper examines the sensitivity of the Dow Jones Islamic market index and its corresponding industry equity indices to changes in the level, slope and curvature of the U.S. term structure of interest rates over the period 1996–2015 using the quantile regression approach. The empirical results reveal that the Islamic stock market has a considerable negative exposure to interest rate risk, although a declining time pattern of interest rate sensitivity is observed. The unexpected changes in the level factor of the U.S. yield curve, closely linked to long-term interest rates, are identified as the most important interest rate factor in explaining the variability of Islamic equity returns. Furthermore, the interest rate exposure tends to be stronger during extreme bearish conditions in the stock market, possibly due to the greater pessimism and risk aversion under these market circumstances. It is also shown that Islamic equities are not different from their mainstream counterparts in terms of interest rate sensitivity, indicating that the Islamic stock market does not provide a cushion against interest rate risk.     

Does inflation cause gold market price changes? evidence on the G7 countries from the tests of nonparametric quantile causality in mean and variance

This article utilizes the newly proposed nonparametric causality-in-quantiles test to examine the predictability of mean and variance of changes in gold prices based on inflation for G7 countries. The causality-in-quantiles approach permits us to test for not only causality in mean but also causality in variance. We start our investigation by utilizing tests for nonlinearity. These tests identify nonlinearity, showing that the linear Granger causality tests are subject to misspecification error. Unlike tests of misspecified linear models, our nonparametric causality-in-quantiles tests find causality in mean and variance from inflation to gold market price changes between the 0.20 quantile and the 0.70 quantile, implying that very low- and high-price changes in gold markets are not related to inflation. These changes should be related to other sources, such as financial shocks and exchange market shocks. We find support that gold serves as a hedge against inflation, but only in the mid-quantile ranges, i.e. quantiles from 0.20 to 0.70. Our results show that gold does not serve as a hedge against inflation during periods when gold market price changes are very low or very high, which are respectively quiet and highly volatile periods.     

Diverse twins: analysing China’s impact on Italian and German exports using a multilevel quantile regressions approach

Germany and Italy are the largest manufacturing producers in Europe and export over 70% of their products to OECD countries. While they share many characteristics, they are also diverse in term of specialization and destination markets. Italy has a productive structure largely based on labour intensive sectors, while Germany is mainly specialized in high-tech goods. We study whether these characteristics make the two countries vulnerable in different ways to the competitive pressure by emerging economies, especially China, which experienced the strongest increase in export market share during the last decades. We discuss the impact of China on the export performance of Italy and Germany on OECD markets. Using data for the period 1995–2009, we implement a novel model to account for two important data characteristics: their hierarchical hidden structure (captured by a multilevel model) and the heterogeneity of the export shares (captured by a quantile approach). Results show that Chinese competition on Italy’s and Germany’s market shares differ by sectors, but, on average, Italy is not more vulnerable than Germany. These results are relevant for policy implications and for an ex-post analysis of the ‘best response’ to the Chinese competition.     

Economies of scale in Norwegian electricity distribution: a quantile regression approach

In this article, we investigate scale economies in Norwegian electricity distribution companies using a quantile regression approach. To the best of our knowledge, this is the first attempt to apply this estimation technique when analysing scale economies. We estimate the cost elasticities of the two output components: network length and number of customers, to calculate returns to scale. Our results show large potential of scale economies, particularly for the smallest companies. We also find that returns to scale is increasing over time. These findings have important implications for policymakers when they are deciding the structure of the industry in the future.     

The impact of income,economic openness and interest rates on housing prices in China: evidence from dynamic panel quantile regression

The rapid growth of housing prices has attracted the attention of the whole of society in China. This article adopts the dynamic panel quantile regression to investigate the impact of income, economic openness and interest rates on housing prices in China, based on the panel data of 35 major cities from 2002 to 2012. Compared with previous studies, we can more precisely and reasonably discuss the impact of these variables on different levels of housing prices. The empirical results indicate that the impact of independent variables on housing prices is heterogeneous across quantiles. Specifically, the impact of income is positive and significant across quantiles, and the impact becomes greater at the 90th and 95th quantiles. Economic openness has a positive and significant effect at the 5th–80th quantiles, which support the Balassa–Samuelson effect, but it is insignificant at the 90th and 95th quantiles. The impact of interest rates is positive and significant at low quantiles, but the impact is negative and insignificant at high quantiles. Furthermore, we also find that the coefficients of interest rates at various quantiles are smaller. In addition, the population has a significant positive effect across quantiles. Finally, we provide important policy implications.     

Who benefits most from property assessment taxes? Evidence from Los Angeles County

Assessment caps on property taxes are often assumed to benefit affluent homeowners the most with little gains for low-income households. Quantile regression results for Los Angeles County show that on average effective property tax rates decrease by $1994 per year due to length of ownership in the 50th percentile because of California’s Proposition 13 assessment cap. There is evidence of both horizontal and vertical inequity across the entire sample. Low-income households do benefit from California’s assessment cap as they are typically infrequent movers but their effective tax rates decrease over time. However, the most affluent households by market value do not gain the most and there is no evidence of horizontal inequity for these homeowners. There is also no evidence of horizontal inequity for middle-income households. Property tax savings vary between $18,000 and $40,000, depending on the assessed value decile and percentage quantile.     

Recent developments of the autoregressive distributed lag modelling framework

We review the literature on the autoregressive distributed lag (ARDL) model, from its origins in the analysis of autocorrelated trend stationary processes to its subsequent applications in the analysis of cointegrated non-stationary time series. We then survey several recent extensions of the ARDL model, including asymmetric and non-linear generalisations of the ARDL model, the quantile ARDL model, the pooled mean group dynamic panel data model and the spatio-temporal ARDL model.     

What has caused China’s economic growth?

Economic growth is driven by numerous factors. However, traditional economic theory focuses on certain key reasons, while ignoring the impact of other factors. Since 1978, China has achieved unprecedented economic growth, but also faces low per capita GDP. To clarify the driving forces behind this situation, we used per capita GDP to represent China’s economic growth and performed total factor analysis based on 13 variables in 7 socioeconomic dimensions using panel data from 30 Chinese provinces over the 40 years since China opened to the west in 1978. We found similar determinants in different regressions. Internal trade, privatization and investment were the primary factors driving Chinese economic development. Surprisingly, we found that the contribution of foreign trade to economic growth (per capita GDP) was weak. Education had a much smaller contribution than science and technology. Using per capita income as the dependent variable to provide a robustness test, we found that China’s income distribution has not paralleled its economic development and the distribution of the benefits of GDP growth to citizens must be improved. China’s experience demonstrates that promoting economic growth requires coordinated development of many factors, and that different policy preferences should be adopted to meet different economic development conditions.     

Cost of abating excess nitrogen on wheat plots in France: An assessment with multi-technology modelling

We use a multi-equation model of polluting technologies to evaluate excess nitrogen's marginal abatement cost (MAC). The MAC is estimated using the convex non-parametric quantile regression. The empirical application is conducted at the plot level for wheat production in France in 2017. Results show a median shadow price for excess nitrogen of about €21 per kilogram. If the current European Union's Nitrates Directive (which sets a 170-kg constraint on organic nitrogen per hectare) were extended to mineral nitrogen, this would allow a reduction of total excess nitrogen by 9.5%, but this would be accompanied by a 3.1% decrease in wheat revenue.