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Italy has been the first Western Country to suffer a massive outbreak of COVID-19. Starting from the 11^th of March 2020, the Italian Government approved a series of emergency restrictive measures to limit people’s movement and social contacts. The aim of this short paper is to test if the number of norm-violations (related to people’s movement) might contribute to the peaks of new COVID-19 positives after few days. We show that peaks in the violations of the lockdown norms correspond to peaks in new positive cases about 6 days later.

The purpose of this paper is to estimate the impact of the 2008 and 2020 economic crises on employment in Spain.

The authors perform a counterfactual analysis, combining intervention (interrupted time series) analysis and conditional forecasting to estimate a “crisis-free” scenario. These counterfactual estimates are used as a synthetic control, to be compared with the observed values of the main variables of the Spanish Labor Force Survey (EPA).

The authors measure the effect on Spanish employment of the 2008 recession and the ongoing COVID/Ukraine crisis and the speed of recovery, which yields a rigorous dating for the beginning and end of the crises studied. Finally, the authors provide estimates about which part of the employed and unemployed people was in furlough (ERTE) based on microdata provided by the Spanish Institute of Statistics.

To the best of the authors’ knowledge, there are no counterfactual studies covering all the basic variables in EPA and no estimates for the effect of ERTEs on the basic employment variables. Finally, the authors combine well-known intervention and forecasting techniques into an integrated framework to assess the effects of both, past and ongoing crises.

Building on recent advances in inverse probability weighted identification and estimation of counterfactual distributions, the authors examine the history of wage earnings for women and their potential wage distributions in the United States. These potentials are two counterfactuals, what if women received men’s market “rewards” for their own “skills,” and what if they received the women’s rewards but for men’s characteristics? Using the Current Population Survey data from 1976 to 2013, the authors analyze the entire counterfactual distributions to separate the “structure” and human capital “composition” effect. In contrast to Maasoumi and Wang (2019), the reference outcome in these decompositions is women’s observed earnings distribution, and inverse probability methods are employed, rather than the conditional quantile approaches. The authors provide decision theoretic measures of the distance between two distributions, to complement assessments based on mean, median, or particular quantiles. We assess uniform rankings of alternate distributions by tests of stochastic dominance in order to identify evaluations robust to subjective measures. Traditional moment-based measures severely underestimate the declining trend of the structure effect. Nevertheless, dominance rankings suggest that the structure (“discrimination”?) effect is bigger than human capital characteristics.

The role of patents for appropriating (capturing) value from innovation investments has for decades been of major interest to both practitioners and academics in innovation management. Many studies have implicitly assumed that firms appropriate value through in-house creation and marketing of innovative products and services, and that the main function of patents is to protect the exclusive sales in product and service markets. We challenge this assumption in light of the variety of business models, strategies and markets now being available, including different organizational and market forms of open innovation.

A conceptual framework and typology of open innovation markets is developed, and the role of patents for appropriation is investigated in these markets among 172 Swedish technology-based firms.

The results show that the importance of patents has a skewed distribution with some firms rating patents very important and with a fat tail of firms rating patents less important. Most importantly, the results indicate that patents are enabling exchange and technology trade in various types of open innovation markets rather than only supporting vertically integrated business models. Thus patents were found to help rather than hinder the use of open innovation markets.

The paper makes two main contributions. First a theoretical reinterpretation of open innovation with a conceptualization of open innovation markets for appropriation of innovation values. Second an empirical illustration of new roles of patents for appropriating innovation values in these markets. The paper in addition illustrates the use of a counterfactual approach to questionnaire surveys, as well as the complementarities between patents and other means of appropriation.

The purpose of this paper is to critically reflect and offer insights on how to justify the use of qualitative comparative analysis (QCA) as a research method for understanding the complexity of organizational phenomena, by applying the principles of the neo-configurational approach.

We present and critically examine three arguments regarding the use of QCA for management research. First, they discuss the need to assume configurational theories to build and empirically test a causal model of interest. Second, we explain how the three principles of causal complexity are assumed during the process of conducting QCA-based studies. Third, we elaborate on the importance of case knowledge when selecting the data for the analysis and when interpreting the results.

We argue that it is important to reflect on these arguments to have an appropriate research design. In the true spirit of the configurational approach, we contend that the three arguments presented are necessary; however, each argument is insufficient to warrant a QCA research design.

This paper contributes to management research by offering key arguments on how to justify the use of QCA-based studies in future research endeavors.

What is the relation between the land system with Chinese characteristics and the country's high-speed economic growth in the past decades? There is a lack of rigorous academic research based on the general equilibrium theory of macroeconomics on this issue.

By building a multisector dynamic general equilibrium framework with land system, this paper explores how the land supply mode with Chinese characteristics affects China's economic growth as well as its transmission mechanism.

This paper confirms the importance of land system with Chinese characteristics in explaining the mystery of China's high-speed economic growth. Counterfactual analysis shows that if China adopts a land system similar to that of other developing countries, GDP will drop 36% from the current level under the baseline model.

As the industrial sector shrinks relatively and the output elasticity of infrastructure decreases, this inhibitory effect will become more apparent. China should improve its land supply mode, especially expand the supply of commercial and residential land and reduce the cost of land in the service sector. This can promote better economic development in the future and thus improve household welfare and the structure of aggregate demand, replace “land-based public finance” and thus inhibit the “high leverage” risks of local governments.

Legislation plays a vital role in solving carbon emissions reduction and climate change issues. China began to implement a low-carbon economic policy in 2010, but the effect of the policy needs to be evaluated. Accordingly, this paper aims to discuss China’s low-carbon policy through exploring the following two questions, namely, whether the policy effect reaches the expected goal and whether the policy effects will balance economic development and emission reduction. Then, the paper puts forward suggestions for the improvement of China’s low-carbon policy.

This paper is organized around three distinct aspects of policy effect evaluation. This paper uses the synthetic control method to construct a policy effect evaluation model and conducts a quasi-natural experiment. The paper selects annual panel data from 2003 to 2015, which is selected from 33 provinces. A comparative analysis of carbon dioxide emissions, energy consumption and economic development between Hubei Province and Liaoning Province.

The results reveal that the implementation of the low-carbon pilot province policy in 2010 has a significant impact on the emission reduction effect of Liaoning Province, but the impact on the emission reduction effect of Hubei Province is not significant. The carbon emission trading system implemented in 2012 has reduced the emission reductions in Hubei Province and Liaoning Province has achieved better emission reduction effects after the implementation of this policy. After the implementation of the policy, the economic development of Hubei Province has been improved, but it has not brought help to the economic development of Liaoning Province. These findings provide new insights into the use of an emissions trading system for improving economic development and ultimately facilitate the attainment of the broader goal of sustainability.

This paper proposes an innovative policy effect evaluation method by considering the status of unit gross domestic product, fixed asset investment in the energy industry, energy consumption, emission reduction technology innovation and other evaluation indicators. This paper contributes to broadening current methods of policy effect evaluation in China.