Value for money in energy efficiency retrofits in Ireland: grant provider and grant recipients

The Sustainable Energy Authority of Ireland (SEAI) administers the Better Energy Homes scheme to provide a financial incentive for home owners to engage in energy efficiency retrofits. This study analyses data from the scheme and Building Energy Rating data for participants to the scheme to examine the value for money achieved by households. In addition, this research identifies which retrofit combinations provide greatest value for money, in terms of energy efficiency gains, for the grant provider. We utilize an error-in-variables approach to model the variation in benefits accruing to households of varying characteristics. We find that household and grant provider surplus can be maximized in the short term by retrofitting less energy efficient and larger homes, timber or steel frame homes and houses rather and apartments. The types of retrofits leading to the greatest surplus for both household and grant provider include cavity wall insulation paired with either a boiler with heating controls or heating controls only retrofit.     

A Meta‐Analysis on the Elasticity of Demand for Pesticides

There is an increasing policy interest in pesticide taxation schemes as a measure to reduce harmful effects of pesticide use. The effectiveness of such tax depends, however, on the price elasticity of demand for pesticides. Moreover, information on these demand elasticities and their determinants is of crucial relevance for policy‐making and normative modeling approaches. In this article, we present a meta‐analysis based on studies that have estimated pesticide demand elasticities in Europe and North America. Our meta‐analysis reveals that the own‐price elasticities of demand for pesticides are, with a median of ?0.28, significantly smaller than zero, but also significantly larger than ?1, i.e. to be inelastic. We find that the demand for pesticides for special crops is less elastic than that for arable and grassland. In addition, the demand for herbicides is more elastic than for other pesticides. Studies that consider only short‐term horizons and little flexibility for farmers to adjust to price changes generate significantly less elastic pesticide demands. The results also indicate that more recent studies identify lower pesticide price elasticities of demand. Furthermore, we find that peer‐reviewed studies tend to find more inelastic results compared to grey literature.     

Determinants of bankruptcy regime choice for Canadian public firms

Distressed Canadian public firms usually file for bankruptcy protection under either the Bankruptcy and Insolvency Act (BIA) or the more flexible Companies Creditors Arrangement Act (CCAA). The latter targets reorganization while the BIA focuses on both reorganization and liquidation. This paper examines the factors that enter into the choice of either of these two regimes by bankrupt filing public firms. We document that firms are more likely to file under the CCAA when the global stock market is bullish. Larger firms, more leveraged firms and firms with higher quality bankruptcy trustees are more likely to file under CCAA. The worst performing firms also tend to file under the CCAA. Finally firms in Ontario and Quebec have a tendency to file more frequently under the BIA compared to other provinces.     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis

This paper aims at analyzing the degree and structure of interdependencies in terms of volatility (transmission, contagion) between Islamic and conventional stock markets on calm periods and at times of financial fragility and crisis. We focused on the recent financial instability periods and used the Quantile Regression-based GARCH model. Main results lead to very interesting conclusions. First, it has been found that Islamic stock markets are not totally immune to the global financial crisis. Second, a very strong interdependence is sensed from the conventional to the Islamic stock markets, especially, from the conventional developed markets to the Islamic Emerging and Arab markets and to the Islamic developed markets. Finally, it has been proved that the interdependencies from conventional to Islamic markets are propagated between Islamic markets. Our findings suggest that the Islamic finance industry does not seem able to provide cushion against economic and financial shocks that affect conventional markets.     

ON THE CONSISTENCY OF REGRESSION‐BASED MONTE CARLO METHODS FOR PRICING BERMUDAN OPTIONS IN CASE OF ESTIMATED FINANCIAL MODELS

In many applications of regression‐based Monte Carlo methods for pricing, American options in discrete time parameters of the underlying financial model have to be estimated from observed data. In this paper suitably defined nonparametric regression‐based Monte Carlo methods are applied to paths of financial models where the parameters converge toward true values of the parameters. For various Black–Scholes, GARCH, and Levy models it is shown that in this case the price estimated from the approximate model converges to the true price.     

Stock Price Index and Exchange Rate Nexus in African Markets

This paper examines the relationship between stock price index and exchange rate in six African markets using monthly data for the period January 2007 to October 2015. A quantile regression approach is used. This methodology is shown to perform better than the ordinary least squares estimators, particularly when the conditional distribution is heterogeneous. Our empirical evidence reveals an interesting pattern in the association of these two financial markets in Africa, which shows that the negative relationship between stock and foreign exchange markets is more apparent when exchange rates are extremely low or high. The negative relationship between the two variables is in line with the portfolio balance effect.     

城市化进程中的“资源尾效”和“资源诅咒”——基于中国27个煤炭城市的面板数据分析

传统城市化理论往往强调自然资源对城市发展的正面作用,却对城市化的约束和反向作用问题考虑不够。文章基于"资源尾效"和"资源诅咒"两种假说,利用1997-2012年中国27个典型煤炭城市的数据对其煤炭资源开发与城市化发展的关系进行正负效应检验。结果表明:27个煤炭城市中有16个城市出现"资源尾效",其尾效数值为0.001 755;其余11个城市出现"资源诅咒",其煤炭资源对城市化发展的影响系数为-0.207 2。可见,自然资源的开发强度要处于一个合适的水平,并同时注意资本投入、教育和制度等因素才能最大程度上提高城市化水平。     

职场友谊对研发团队创新绩效的影响机制研究——一个带中介的调节模型

本文通过问卷调查法获得372份有效问卷，运用带中介的调节模型探讨了职场友谊对研发团队创新绩效的影响机制。实证结果表明：（1）职场友谊对团队创新绩效是有正向的激励作用的，其中知识分享起中介作用；（2）职场友谊对团队创新绩效的作用同时受到员工知识分享意愿和知识分享能力的中介作用；（3）职位级别对职场友谊通过知识分享对团队创新绩效的影响起负向调节作用，即职位级别越高，友谊机会越小，通过员工友谊促进知识分享，进而提高团队创新绩效的效应越低。     

工业集聚与污染排放强度——基于固定效应门限回归模型的再检验

为研究工业集聚对污染排放强度的影响，本文选取2000~2015年全国30个省市（自治区）的面板数据，以工业集聚为门槛变量，利用固定效应门限回归模型，实证分析了不同工业集聚水平对污染排放强度的影响。结果发现：工业集聚对废水排放强度的影响存在显著门槛效应，在达到门槛值前，工业集聚很大程度降低了废水排放强度，在跨过门槛值后，这种作用会减弱。工业集聚与废气排放强度呈显著倒“U”型关系，在工业集聚水平小于门槛值时，工业集聚会加剧废气排放，大于门槛值后，工业集聚会降低废气排放强度。工业集聚会降低废物排放强度，但未出现显著门槛效应。