HOW DO POLICY‐MAKERS ACTUALLY SOLVE PROBLEMS? EVIDENCE FROM THE FRENCH LOCAL PUBLIC SECTOR

This article examines how policy-makers solve problems within local representative democracies. It will be argued that politicians cannot undertake an exhaustive search of all possible policy choices; instead, they might use an incremental strategy such as the hill-climbing heuristic. These possibilities will be formalized using the median voter model as an analytical framework. The corresponding models will then be estimated over a set of French jurisdictions (the départements ). The empirical results lend support to the hill-climbing model , given that: (1) for social welfare and secondary school expenditures, the influence of the past is significant; (2) a pure model of incrementalism, without any exogenous variables, is not appropriate for explaining the behavior of departmental council members; and (3) the impact of the past is more significant and stronger when expenditure levels are higher.     

On the Cost of Opportunistic Behavior in the Public Sector: A General‐Equilibrium Approach

This paper studies the wasteful effect of bureaucracy on the economy by addressing the link between opportunistic behavior of government bureaucrats and the public sector wage bill. In particular, public officials are modeled as individuals competing for a larger share of those public funds. A simple extraction technology in the government administration is introduced in a standard real‐business‐cycle setup augmented with detailed public sector. The model is calibrated to German data for the period 1970–2007. The main findings are: (i) the model performs well vis‐à‐vis the data; (ii) due to the existence of a significant public sector wage premium and the high public sector employment, a substantial amount of working time is spent in opportunistic activities, which, in turn, leads to significant losses in terms of output; and (iii) the model‐based loss measures obtained for the EU‐12 countries are highly correlated to indices of bureaucratic inefficiency.     

国内外煤炭价格波动特征分析——基于GARCH模型

利用2005—2011年的澳洲BJ动力煤价格和秦皇岛大同优混煤(>6000大卡)价格的时间序列数据,采用GARCH模型分析方法,实证检验了澳洲BJ动力煤价格和秦皇岛大同优混煤(>6000大卡)价格的波动性特征。研究结果表明,澳洲BJ动力煤价格和秦皇岛大同优混煤(>6000大卡)价格表现出相同的市场特性,具有显著的GARCH效应与波动聚集性,波动衰减缓慢,不具有显著的非对称性波动。最后提出了相应的对策与建议。     

我国城镇居民的健康需求与Grossman模型——来自截面数据的证据

本文从人力资本的角度用Grossman模型来分析我国城镇居民的健康需求。利用中国健康和营养调查(2000)数据,我们有以下主要发现:(1)与收入的不平等形成对比,城镇居民健康状况的分布比较均衡;(2)女性的教育程度对健康有正的影响,而男性的教育程度对健康的影响不显著;(3)年龄对男性健康的影响比女性大;(4)收入或工资水平对健康的影响不显著。总体而言女性比男性更符合Grossman模型的预测。     

Which is the best: A comparison of asset pricing factor models in Chinese mutual fund industry

Factor models are commonly used in estimating risk-adjusted fund performance. We compare the commonly used factor models in empirical asset pricing studies and find that Fama and French (2015) five-factor model outperforms other models in the Chinese mutual fund industry and in most fund segments. The factor models we tested are more effective in explaining the return of index funds than other types. Meanwhile, we also find that the capital asset pricing model (CAPM) better controls the estimated alpha dispersion than other models. Though most multifactor models including Carhart (1997) have higher R-squared than CAPM, the cross-sectional differences between them are not statistically significant.     

Cross-sectional and time-series momentum returns and market dynamics: evidence from Japan

We test the behavioural theories of overconfidence and underreaction on cross-sectional (CS) and time-series (TS) momentum returns in the Japanese stock markets. Both CS and TS momentum returns are large and significant when the market continues in the same state and turns into losses when the market transitions to another state, consistent with the overconfidence but not the underreaction model. We find that TS conditional momentum returns exceed conditional CS momentum returns because of its active position since TS takes a net long (short) position following UP (DN) markets while CS is a zero-cost strategy irrespective of the market state. Finally, we find no relation between idiosyncratic volatility (IV) and momentum returns which is not supportive of either the overconfidence or underreaction model but implies that IV is not a significant limit to arbitrage in Japan.     

Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

Estimates of Capital Stock and Capital/Output Coefficients by Industries: Korea (1953–86)

This paper constructs a polynomial-benchmark model to estimate gross and net capital stocks by explicity estimating implicit retirement rates and depreciation rates. The model is applied to Korean data (1953–86) where such data as national wealth survey, national income accounts and industrial census are available. There alternative series of capital stock estimates are generated and compared with previous estimates. It is shown that the use of a pure perpetual-inventory model or a benchmark-year method alone may introduce a significant bias in the measurement of capital stocks for developing economies.     

中国新凯恩斯菲利普斯曲线研究

本文提出了包含需求拉动、成本推动、通胀预期和通胀惯性四种因素的新凯恩斯菲利普斯曲线模型,该模型推广了Gordon(1996)的三角模型和Gaíland Gertler(1999)的混合模型等经典菲利普斯曲线模型,具有理论上的完整性。本文使用中国数据对所提出的模型进行了检验,其中采用了基于微观调查数据的通胀预期。经验研究结果表明,新凯恩斯菲利普斯曲线模型的最小二乘估计比GMM估计更具有稳健性。在通胀的四个决定因素中,通胀预期对当前通胀的影响最显著,通胀惯性次之,需求拉动排第三,而成本推动的影响不显著。     

全球化和中国经济增长关系的实证分析

通过对全球化和中国经济增长关系的实证分析,可以发现:(1)在1978—2002年的长周期样本中,经济全球化对中国经济增长的影响不显著;(2)在20世纪80年代,经济全球化推动了中国资本—劳动比和TFP的提高,进而推动中国的经济增长,20世纪90年代以后,这种影响逐步消失;(3)经济全球化与中国经济增长关系的"时变特征"源于中国经济增长阶段和增长模式的变化。     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

Adapting and testing the Fama and French model,with some variations of company characteristics

We examine whether the Fama and French (1992) (F&F) model can be adapted to become a more versatile and flexible tool, capable of incorporating variations of company characteristics in a more dynamic form. For this, the risk factors are reconstructed at the end of each reading of monthly data. We argue that, over time, the evaluation of a company may change as a result of variations in its market price, size or book price, and we are aware that the F&F model does not accurately reflect these dynamics. Our results show that the adapted model is able to capture the behaviour of a greater number of stocks than the original F&F model and risk factors are more significant when building them through our procedure. In addition, we carry out these adaptations during a period of instability in financial markets.     

Labour participation in Colombia

A model is estimated for the decision of participating in the labour market for different groups of household members: not coupled (single, divorced and widow) women and men and coupled (married and in permanent union) women and men. The differences among these groups are significant. Probit models are estimated for the period 1984?:?1–2000?:?4 using the National Housing Survey. The neoclassical static model performs fairly well in describing the empirical determinants of the decision of participating. In terms of sign and significance of estimated coefficients the best performance of the model is reached for women. In terms of prediction the model proves useful for not coupled persons. Except for the variable named ‘children aged less than six years’, all variables perform well.     

The Stabilizing Effect of Industrial Structure Upgrade on Economic Fluctuations in China

Empirical study using a time-varying parameter model indicates that since the reform and opening up of China,its industrial structure upgrade has had an increasingly significant stabilizing effect on the amplitude of economic fluctuations.A further analysis using a TGARCH model reveals that the three major industrial sectors have asymmetrical effects on the size of macroeconomic fluctuation:the primary industry(extraction)has little effect;the secondary industry(manufacturing)has a leverage effect mainly caused by heavy industry;the tertiary industry(services)has a clear stabilizing effect,with the effect of transportation,logistics,the postal industry,housing-catering services,and other service industries being most significant,and the effect of wholesale,retail,the finance industry and real estate being less significant due to their own large fluctuations.The policy implications of the findings are that to maintain stable growth in the economy,China should optimize the relations of the three major industrial sectors,and further push for the upgrading of the industrial structure,especially the development of the tertiary industry.     

A Bayesian approach to misclassified binary response: female employment and intimate partner violence in urban India

We examine the effect of female employment on the odds of physical spousal violence using a Bayesian misclassification model combined with propensity score regression estimation. While a classical propensity score model finds a significant violence-provoking effect of female employment, our model finds no evidence of a significant effect. This suggests that misleading inferences are caused by falsely small standard errors in a model that does not account for uncertainties around propensity scores. Further, we confirm our misclassification model as a preferred specification using Deviance Information Criterion (DIC).     

Exports and economic growth in Central and East European countries during transition

This paper quantifies the contribution of exports to economic growth in Central and East European countries (CEECs) during transition. Two theoretical models are examined: the first is based on an aggregate production function which includes exports as an additional ‘input’; while the second is based on a two-sector (exports and non-exports) model where exports provide positive externalities in non-export production. Each model is estimated with both fixed and random effects using panel data. Results show that the random effects model is preferred and that exports have a significant impact on economic growth.     

The structure of production in South Korea's manufacturing sector

This paper estimates a model of producer behavior for South Korean manufacturing that simultaneously identifies substitution elasticities and scale economies. A non-homothetic translog function is employed which takes on various other functional forms (i.e., Cobb–Douglas, Homothetic, Homogeneous) as special or limiting cases. Four significant conclusions are: (a) there is potential scale economies in each subsector of South Korean manufacturing, (b) the substitutabilities between factor inputs are relatively low, (c) factor demands are price elastic, (d) the scale economies are correlated with the factor intensity.     

Market structure and the cost of capital

We contribute to the finance literature in two main ways. First, we present a theoretical capital asset pricing model (CAPM) to price assets in different market structures. Second, we use our model to analyze whether when markets are partially segmented using the local or the global CAPM yields significant errors in the estimation of the cost of capital for a sample of firms from developed and emerging countries.     

The Phillips Curve, the IS Curve and Monetary Transmission: Evidence for the US and the Euro Area

In this paper we assess the empirical performance of commonlyused empirical specifications of the baseline New Keynesianmodel for the US and the euro area. We estimate standard specificationsof the model and extended specifications also including non-standarddeterminants of aggregate supply and demand. The results suggestthat based on the standard specifications it is often not possibleto establish a significant link between the monetary policyinstrument and output and inflation. Based on the extended specificationsof the model, which take into account the significant effectof commodity prices on inflation and of house prices on theoutput gap, we are generally able to restore a significant monetarytransmission channel. (JEL E3, E52, C22)     

Forecasting the oil futures price volatility: A new approach

This study provides a new perspective of modelling and forecasting realized range-based volatility (RRV) for crude oil futures. We are the first to improve the Heterogeneous Autoregressive model of Realized Range-based Volatility (HAR-RRV) model by considering the significant jump components, signed returns and volatility of realized range-based volatility. The empirical results show that the volatility of volatility significantly exists in the oil futures market. Moreover, our new proposed models with significant jump components, signed returns and volatility of volatility can gain higher forecast accuracy than HAR-RRV-type models. The results are robust to different forecasting windows and forecasting horizons. Our new findings are strategically important for investors making better decisions.