A new look at variation in employment growth in Canada: The role of industry,provincial, national and external factors

We examine fluctuations in employment growth using Canadian data from 1976 to 2010. We consider a wide range of models and examine the sensitivity of our findings to modelling assumptions. The results from our most preferred model, which we selected using the Bayesian Information Criteria, indicate that most of the variance in employment growth that is not due to the idiosyncratic error comes from domestic sources, with most of this coming from industry and provincial factors. Overall, we find that external and national factors play a much smaller role in employment fluctuations than in earlier research. We provide some possible explanations for these differences and discuss the implications of our findings for public policy and theory.     

Forecasting macroeconomic variables in emerging economies

Forecasting macroeconomic variables in rapidly changing emerging economies presents a number of challenges. In addition to structural changes, the time-series data are usually available only for a short number of periods, and predictors are available in different lengths and frequencies. Dynamic model averaging (DMA), by allowing the forecasting model to change dynamically over time, permits the use of predictors with different lengths and frequencies for the purpose of forecasting in a rapidly changing economy. This study uses DMA to forecast inflation and growth in Vietnam, Thailand, Philippines, Sri Lanka and Ghana. We compare its forecasting performance with a wide range of other time-series methods. We find that the size and composition of the optimal predictor set changed, indicating changes in the economic relationships over time. We also find that DMA frequently produces more accurate forecasts than other forecasting methods for both inflation and economic growth in the countries studied.     

Do constraints created by economic growth targets benefit sustainable development? Evidence from China

An economic growth target is a declaration by policy authorities of commitment to that target and the corresponding allocation of resources. The constraints created by economic growth target are an important economic management method in China, which has helped China's economy to achieve remarkable achievements. However, it has also brought about serious environmental problems, threatening China's sustainable development. Using the data about economic growth targets in the work reports of 30 Chinese provincial governments from 2006 to 2017, this paper constructs several spatial measurement methods, such as the spatial Durbin model, to examine the constraints created by economic growth target's impacts on air pollution. The main conclusions are as follows. First, a significant “U-shaped” relationship exists between the constraints created by economic growth targets and air pollution. Second, the spatial Durbin model analysis revealed that PM_2.5 across China's provinces display significant positive spatial spillover effects and spatial agglomeration characteristics. Third, the direct, indirect, and total effects of constraints created by economic growth targets on air pollution are all statistically significant and depict a “U shape.” Finally, the constraints created by economic growth targets have an apparent threshold effect on air pollution, and the inhibiting effects increase with human capital and industrial restructuring. However, with the increase in foreign direct investments, constraints created by economic growth targets may increase air pollution. The conclusions of this paper are of great significance for improving the management of local government economic growth targets and sustainable development.     

Food scandals,media attention and habit persistence among desensitised meat consumers

Consumer reactions to food scandals and their resulting economic implication are well documented. However, studies have typically neglected the roles that consumption habits and media usage behaviours may play in explaining household’s response to food safety incidences. In this study we develop a model of heterogeneous media usage intensity, information impacts and decay over time to estimate household’s behavioural responses to the 2011 German Dioxin scandal. We are specifically interested in determining the degree of heterogeneity in household’s short-term adjustments demand patterns versus persisting long-term consumption habits of meat products (chicken and pork) directly affected by the incident. The empirical analysis employs detailed household-level retail scanner and media usage data collected by the GfK Consumer Scan panel for a total of 16,023 households over a period of 104 calendar weeks. Results of dynamic correlated random effect Tobit models indicate an important role of unobserved heterogeneity in explaining household responses during the food scandal. We find strong empirical evidence supporting our hypothesis that short-term marginal adjustments in demand and propensity to buy affected products triggered by the negative impact of household media exposure were over-compensated by habit persistence. The question of how consumption patterns evolve over time in the presence of food scandals is expected to be of interest for both policy makers and the food industry. The potential biases in the projection of economic impacts resulting from simplifying assumptions of household’s response patterns to a proliferating numbers of food safety incidences has implications for risk management and public policy.     

How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons

This study investigates the role of hedging and portfolio design among stocks, exchange rates, and gold in small open economies (SOEs) from 4 January 2000 to 31 March 2020. We adopt the trivariate dynamic conditional correlation-fractionally integrated asymmetric power ARCH model and unconditional quantile regression model, and our findings show that the hedging role of the U.S. dollar (USD) and gold against stocks differs under regular and extreme market conditions. The USD can act as a powerful hedge asset for stocks in regular market periods. Moreover, during the global financial crisis and COVID-19 outbreak, the safe-haven effect of gold becomes stronger for almost all stocks, whereas the USD can serve as a strong safe haven against stock markets of Korea, Taiwan, and Singapore when stock returns are extremely low. In terms of portfolio designing, we find that adding the USD and gold to portfolios improves their hedging effectiveness, and the optimally weighted stock-USD-gold portfolio is the best portfolio strategy, irrespective of referring to return or risk.     

Noisy signaling in discrete time

This paper characterizes the equilibrium set of a dynamic noisy-signaling model in discrete time. A seller privately knows the quality of her asset. She can exert a costly effort to generate stochastic returns. Buyers stochastically arrive over time and, after observing the history of returns, they make price offers. In our model, the equilibrium behavior of the buyers is discontinuous: they only make acceptable (high) offers if the posterior about the quality is above a given threshold. As a result, the recursive nature of the model replicates the discontinuity, giving the equilibrium continuation payoff a complex self-replicating structure that may take the form of a devil’s staircase.     

退耕还林背景下农户收入的社会网络效应分析 ——以四川南江县白滩村为例

研究目的:探讨退耕农户在生产力安排和收入结构方面是否存在同群效应或者互补效应,以及劳动力流动、退耕还林政策因素对农户收入结构的影响机制。研究方法:考虑农村社会网络内部农户间互动对其决策的影响,利用空间权重矩阵精确且全面地捕捉和定位社会网络复杂关系,构建空间计量模型展开分析。研究结果:(1)在白滩村社会网络体系中,农户的农业收入比增长1%,其亲戚邻居的家庭农业收入比降低6.7%,这一情况反映了劳动力由农业部门向非农部门转移而产生的社会网络"互补效应";(2)白滩村退耕程度越高的农户,其农业收入占家庭总收入比例就越高,退耕程度每增加1%,农业收入比将提高5.2%;(3)家庭总劳动力越多的,农业收入占总收入比例越低,其中家庭农业劳动力每流出1%,农业收入比减少3.2%。研究结论:(1)将白滩村社会网络的互补效应应用于其农村信息共享平台建设;(2)通过鼓励种植收入较高的经济林提高农民退耕还林积极性;(3)以就业为核心促进白滩村剩余劳动力转移。     

Impact of short selling activity on market dynamics: Evidence from an emerging market

With unique daily short sale data of Borsa Istanbul (stock exchange of Turkey), we investigate the dynamic relationship between short selling activity and volatility, liquidity and market return from January 2005 to December 2012 using a VAR(p)-cDCC-FIEGARCH(1,d,1) approach. Our findings suggest that short sellers are contrarian traders and contribute to efficient stock market in Turkey. We also show that increased short selling activity is associated with higher liquidity and decreased volatility. However this relation weakens during the financial turmoil of 2008. Our results indicate that any ban on short sales may be detrimental for financial stability and market quality in Turkey.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.     

Agricultural productivity growth in Latin America and the Caribbean: an analysis of climatic effects,catch‐up and convergence*

This paper investigates whether climatic adjusted total factor productivity (CATFP) in Latin America and the Caribbean (LAC) is converging, converging to different steady states or exhibit absolute convergence, that is the process does not require (government) interventions to reach its equilibrium path. We use data from the University of East Anglia’s Climatic Research Unit and from the Food and Agriculture Organization for 28 LAC countries over a 54‐year period (1961–2014) to estimate random parameters stochastic production frontier models to calculate CATFP and then use cross‐sectional regressions and an error correction model to analyse CATFP convergence across countries in the region. The results show that technological progress is the main driver of CATFP growth in the region and there is no absolute convergence, that is CATFP gaps across countries will not decrease over time and least performing countries will not grow faster than better performing ones without targeted policies. However, CATFP across LAC exhibits conditional convergence towards different steady states. Technological progress plays a critical role in raising the steady state level of CATFP with an overall average of 2.22 per cent per annum.