“Opt out” or kept out? The effect of stigma,structure, selection,and sector on the labor force participation of married women in India

Using the 61st and 68th rounds of National Sample Survey data, we investigate the role of stigma, the economy’s structure, potential selection bias, and sectoral differences in explaining the low labor force participation (LFP) of middle and secondary educated women in India relative to low‐ and high‐educated women (the “U‐shape”). Estimating LFP regressions on a sample of prime‐aged married women, we show that, controlling for background characteristics, if a woman’s husband works in a white‐collar job in a region with a high share of blue‐collar jobs, she is less likely to participate in the labor market (stigma). We also find a positive effect of an increase in an index of white‐collar job growth (structure) on married women’s LFP. These effects are present in both rural and urban sectors but are strongest in the rural sector. However, middle and secondary educated women are still found to have substantially lower LFP than low‐ and graduate‐educated women in both sectors. Indeed, over time, the U‐shape persists in the rural sector and deepens in the urban sector. Because unobservables are quite large in the urban sector, we use the method of instrumental variables and find an increasing return at middle levels but stagnation at higher levels.     

Semiparametric time series regression modeling with a diverging number of parameters

Variable selection and error structure determination of a partially linear model with time series errors are important issues. In this paper, we investigate the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation penalty for a partially linear model with a divergent number of covariates and finite order autoregressive time series errors. Both consistency and asymptotic normality of the proposed penalized estimators are derived. The oracle property of the resultant estimators is proved. Simulation studies are carried out to assess the finite‐sample performance of the proposed procedure. A real data analysis is made to illustrate the usefulness of the proposed procedure as well.     

City Size,Population Concentration and Productivity: Evidence from China

This paper investigates the impact of China's city size and urban population concentration on city productivity by developing a distinctive index based on global nighttime light data. Using the panel data of 280 prefecture cities from 2004 to 2013 and employing dynamic system generalized method of moments and panel threshold model regression techniques, our results show that city size has a positive impact on city productivity; therefore, cities in China still have the potential to expand. While moderate urban population concentration can benefit city productivity, excessively concentrated urban population distribution may impede the growth of city productivity. We also find that the level of labor income significantly affects the impacts of urban agglomeration on labor productivity. Therefore, our results imply that city development policies should focus more on how to appropriately allocate economic activities and adjust population distribution in urban areas according to different stages of economic development.     

Defining Supply Chain Management: In the Past,Present, and Future

The article titled “Defining Supply Chain Management” published in 2001 in the Journal of Business Logistics has been cited over 4,900 times in the last 17 years. In this paper, we first provide a historical review of how the article originated and the contributions the article made to both the theory and practice of supply chain management (SCM). Next, we highlight the key market and technological changes that have emerged in SCM followed by how the theory proposed in the 2001 article can still be relevant to support SCM research and practice going forward. We also propose ways of configuring a supply chain and partnering across companies to serve customers in an optimal way. We conclude with a call for research on developing new frameworks to better describe, explain, predict, and shed light on the evolving nature of SCM.     

Business investment in euro area countries: the role of institutions and debt overhang

The recovery of business investment in the euro area has been sluggish, thereby hampering aggregate demand in the short term and potential growth in the long run. While we show that business investment can be associated to cost and supply of credit, cyclical demand conditions and economic uncertainty. But we also find evidence of additional factors. We suggest that there exists a link between excess leverage and weak economic institutions on the one hand and subdued investment growth on the other hand. Moreover, in euro area countries with both larger excess leverage and weaker economic institutions, the link with business investment is found to be stronger. The link between investment and weak institutions or excess leverage highlights the importance of structural reforms aimed at easing business regulations, reducing administrative burdens and increasing the efficiency of insolvency frameworks. These reforms are thus expected to reduce distortions in the allocation of resources and be supportive of a smoother deleveraging process, hence fostering business investment.     

确权、交易、资产化：对大数据转为生产要素基础理论问题的再思考

大数据是数字经济的基础性、战略性资源，是后疫情时代经济发展的重要生产要素，但社会各界对大数据的理论认知仍落后于其应用实践，而且大数据确权、交易定价、资产化问题也存在诸多争议，这对大数据产业和数字经济的持续健康发展形成潜在隐患，也成为制约大数据向生产要素正常转化并参与社会大生产的关键。文章在对大数据概念、属性重新认识的基础上，综合财经、法律等理论观点和实操技巧，阐述了大数据如何从商品流通要素演变为社会生产要素的市场逻辑以及使用价值如何注入大数据的资产化过程，并从实践视角提出大数据确权的法理基础和大数据交易所生态下交易定价模型。同时提出以数据税来弥补大数据采集环节个人和企业放弃的小微权利，将私权转化为社会公共产品，为大数据产业和要素市场发展提供新的借鉴。     

Are firms ready to use big data analytics to create value? The role of structural and psychological readiness

In this study, we leverage Information Technology (IT) readiness literature and resource-based view (RBV) to investigate the impact of firm structural and psychological readiness on firm value creation, as mediated by big data analytics usage. The proposed research model is empirically validated using survey data from 179 senior IT managers. The findings demonstrate the importance of both structural (i.e. IT infrastructure capability, tools functionality, employee analytical capability, and bigness of data) and psychological readiness (i.e. IT proactive climate) in enhancing firm value creation through big data analytics usage. These results provide interesting theoretical and practical insights.     

Intertemporal substitution in the Spanish economy: Evidence from regional data

This paper studies the intertemporal substitution in consumption and leisure for the Spanish economy by estimating the first‐order conditions of an individual optimization model with regional and aggregate data. While first‐order conditions determining intertemporal substitution in consumption show a good econometric fit, and the value we obtain for the intertemporal elasticity of substitution is similar to previously available results, the econometric fit of the intertemporal condition in leisure indicates that the behaviour of the Spanish labour supply over the cycle is more complex than can be explained by the canonical intertemporal choice model.     

International heterogeneity in the associations of new business models and broadband Internet with music revenue and piracy

Broadband Internet has fundamentally changed business models in many industries. In the music industry, for instance, old business models were challenged by illegal competitors, and broadband Internet has enabled value creation through new business models. The changes that established business models experienced in the wake of broadband Internet, however, differed vastly across national markets, and these differences are not well understood. We build a conceptual framework and study the extent to which differences in economic and cultural factors are associated with different market outcomes in the wake of the proliferation of broadband Internet. Thus, we compile two unique data sets from the music industry, comprising (1) revenue data for 36 countries and 22 years and (2) piracy data for 47 countries and >2 years. We use a Bayesian multilevel model to explore between-country heterogeneity in the associations between these variables and broadband Internet adoption and business model innovations. Our results show that the negative association between broadband Internet penetration and music revenue is weaker in high-income countries, where income restrictions are less likely to drive demand towards illegitimate piracy services. In terms of cultural factors, we find that a market's response to the introduction of broadband Internet is less negative in countries scoring high on Hofstede's individualism and uncertainty avoidance dimensions. Furthermore, we find that overall revenues only recover after the latest generation of streaming services (e.g., Spotify) has been introduced, and the adoption of these services is associated with lower levels of online music piracy.