ECONOMIC TRANSITION AND LABOUR MARKET DYNAMICS IN CHINA: AN INTERPRETATIVE SURVEY OF THE ‘TURNING POINT’ DEBATE

Has the Chinese economy approached the ‘Lewisian turning point’ that marks the ending of the initial phase of industrial transformation fuelled by surplus labour? In this paper we undertake an interpretative survey of the literature on this issue, in the context of China's labour market conditions prior to the reforms and structural change of the past three decades. The available evidence is mixed, and our assessment makes a strong case for probing institutional constraints to labour mobility from an economy‐wide perspective, going beyond the confines of the rural economy.     

The impact of climate change on labour demand in the plantation sector: the case of tea production in Sri Lanka

Limited opportunities for crop switching and lengthy preharvesting periods make the plantation sector particularly vulnerable to climate change. Surprisingly, however, the economic consequences of climate change on plantation crops are seldom analysed. Drawing on a unique primary panel data set from a representative cross section of 35 tea estates in Sri Lanka over the period 2002–2014, this study implements a structural model of estate profit maximisation to estimate the elasticity of labour demand with respect to different components of weather. Results indicate a negative relationship between labour demand and rainfall in the south‐west monsoon, the north‐east monsoon and the second inter‐monsoon. A positive relationship is found between labour demand and rainfall in the first inter‐monsoon. Overall, predicted changes in rainfall by 2050 are anticipated to reduce labour demand by approximately 1,175,000 person‐days per year across Sri Lanka's tea plantation sector. This is likely to have considerable social and welfare implications, particularly for the Indian Tamil women who comprise the majority of the sector's workforce.     

结构性减税与扩张政府支出的宏观经济效应

为了深入研究不同类型财政政策对宏观经济的影响效应，本文构建纳入异质性家庭和细化财税工具的新凯恩斯DSGE模型，并着重模拟分析了不同类型财政政策冲击对居民消费、私人投资、通胀率以及总产出水平的动态影响效应。研究结果表明，不同类型财税工具对宏观经济的冲击效果存在显著差异，对于税收政策，劳动收入税减税能够有助于提升消费水平和消费需求，并调节和完善消费结构；而对于政府支出政策，转移支付规模的扩张通过刺激家庭消费，引导消费内需有效提升，从而带动经济增长方式由投资驱动型向消费驱动型转变，进而推动经济高质量发展。     

组合式房产税改革的宏观经济效应 ——兼顾居民用房与商业用房的DSGE框架分析

本文通过构建包含房产税的动态随机一般均衡（DSGE）框架，兼顾居民用房与商业用房，模拟分析房产税改革对主要宏观经济变量的影响。研究结果表明：（1）提高居民用房房产税税率对总消费、投资、房价和总产出等变量的均衡值和波动均以负面影响为主，但会降低社会福利损失；（2）降低商业用房房产税税率对总消费、投资、房价和总产出等变量的均衡值和波动均以正面影响为主，但会提高社会福利损失；（3）提高居民用房房产税税率与降低商业用房房产税税率同时实施时，不仅能够对冲居民用房房产税改革对宏观经济的负面影响，尤其是能够有效对冲改革对投资和总产出的负面影响，还会降低社会福利损失。因此，中国下一步试点改革应当重点关注组合式改革方案。     

农户生物菌肥购买意愿及行为的影响因素研究*——基于山东省设施菜农的调研数据

[目的]生物菌肥对于土壤改良、环境改善、食品安全具有重要意义,但目前生物菌肥在整个肥料产业中所占份额较小,迫切需要探讨如何从农户角度提高生物菌肥的施用比例。[方法]基于设施蔬菜农户的数据,构建Bivariate Probit模型,对农户生物菌肥的购买意愿和行为的影响因素进行比较研究。[结果]农户的生物菌肥购买意愿和行为总体上呈现一致性,愿意购买的农户中有97. 77%的农户具有实际的购买行为;但两者的影响因素有所差异,从差异因素来看,质量安全检测对购买意愿具有显著的正向影响,但对购买行为的影响并不显著;农户文化程度、种植年限、对无公害、绿色、有机蔬菜的了解程度,经销商推荐,施肥指导对购买行为具有显著的正向影响。从共同因素来看,生态环境认知变量对购买意愿和购买行为影响不显著。[结论]要推广生物菌肥,需要进一步加强质量安全检测体系对农业行为的约束性,提升经销商的规范经营意识,采用集中招标等灵活的价格政策,提升农户的生态技能,并在保护生态环境方面出台更完善的农业绿色发展政策。     

Evolution of indigenous tourism among the Lacandon of Chiapas: an application of Weaver’s model

ABSTRACT

In this paper, Weaver’s six-stage indigenous tourism model is applied to the Lacandon Maya (Hach Winik) of Chiapas, Mexico. Based on a comprehensive review of the anthropological and historical literature on this indigenous group, combined with longitudinal ethnographic and collaborative research performed with tourism entrepreneurs, the Lacandon tourism experience is assessed from the pre-European period until present. By analysing a case study of indigenous tourism in Mexico, a developing country in another geographical region and with a different colonial past, this work supplements Weavers’ perspective. The results show that the fourth and fifth stages of Weaver’s model coincide in this case study, while the sixth stage is still incomplete. Although the Lacandon case has its peculiarities and bearing in mind that several different factors should be considered in the Latin American context, the model proves to be an interesting tool for indigenous tourism analysis in developing countries.     

Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance

Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology and disease mapping. A common research question in these subjects is modelling the number of disease events per region; here the BYM models provides a holistic framework for both covariates and dependencies between regions. We use these tools to assess the relative insurance risk associated with the policyholders geographical location. A Bayesian modelling approach is presented and an elastic net is used to reduce the large number of possible geographic covariates. The final inference is performed using Integrated Nested Laplace Approximation. The model is applied to car insurance data from If P&C Insurance together with spatially referenced covariate data of high resolution, provided by Insightone. The entire analysis is performed using freely available R-packages. Including spatial dependence when modelling the number of claims significantly improves on the result obtained using ordinary generalised linear models. However, the support for adding a spatial component to the model for claims cost is weaker.     

Should sequels differ from original movies in pre-launch advertising schedule? Lessons from consumers' online search activity

Sequels have become a profitable strategy in the U.S. motion picture industry because of their strong name recognition. However, while the established positioning of a sequel may help insulate it from competing firms' advertising messages, its familiarity may cause moviegoers to be more easily satiated with advertising from the sequel. Therefore, this study examines how sequels differ from original concept movies in terms of their ad effectiveness. We focus our analysis on pre-launch periods, given these periods' importance in shaping the financial outcomes of motion pictures. We consider the weekly online search volume of a movie as a measure of consumer interest in it, and thus as an intermediate response to pre-launch advertising. We then develop a model that assumes ad effectiveness can decline, due to copy and repetition wearout, and increase, due to forgetting, over time. We find that copy wearout is greater for original movies, while repetition wearout and forgetting are greater for sequels. These findings suggest that sequels should allocate more in early pre-launch periods and less immediately before release, relative to originals, to maximize pre-launch consumer interest.     

Factors affecting agricultural land transfer-in in China: a semiparametric analysis

We use interview survey data collected randomly from 2677 farm households in nine provinces of China to understand the role of demographic, economic, land, and village characteristics on agricultural land transfer-in by farmers. Results show that variables such as borrowing from informal sources, household labour availability, percentage of total income from agricultural sources, and the household with village cadre have significant positive effects on land transfer-in. Low economic development and low transportation network availability in a county reduces land transfer-in. We also find that two variables (land holding and land idling) should be entered into the model nonparametrically. Land holding and land idling have U- and L-shaped impacts on land transfer-in, respectively. Land transfer-in has endowment equilibrium and provides Chinese households more opportunities to earn agricultural income, thereby reducing rural poverty.     

Does default point vary with firm size?

This article aims to improve the predictive ability of KMV model by distinguishing firm size. The evidence suggests that default point would vary with firm size. Using the method of particle swarm optimization, we obtain the optimal default point separately for large firms and small firms. Several statistical tests such as the model confidence set methodology show that our relatively tractable model is more likely to have the strongest predictive ability.