International collaboration and innovation: Evidence from a leading Chinese multinational enterprise

This paper investigates the impact of international collaboration and its characteristics on the quality of the innovation of multinational enterprises (MNEs) in emerging markets. Using a unique dataset of 1428 international and comparable domestic collaboration projects over the 2010–2016 period, it finds that while international innovation collaborations are associated with high innovation quality, cultural distance has a negative effect on collaboration outcomes. Moreover, proximity to the focal firm's overseas R&D centres and the size of expenditure budgets play significant moderating roles in overcoming cultural barriers. Based on the RBV and dynamic capabilities theory, we investigate how firms from emerging markets can acquire these two crucial requisites for innovation. The characteristics of partners and intellectual property (IP) arrangements are also found to have a significant impact on the quality of innovations.     

Measuring financial soundness around the world: A machine learning approach

We use a fully data-driven approach and information provided by the IMF’s financial soundness indicators to measure the condition of a country’s financial system around the world. Given the nature of the measurement problem, we apply different versions of principal component analysis (PCA) to deal with the presence of strong cross-sectional and time dependence in the data due to unobserved common factors. Using this comprehensive sample and various statistical methods, we produce an alternative data-driven measure of financial soundness that provides policy makers and financial institutions with a monitoring and policy tool that is easy to implement and update. We validate our index by using alternative macroeconomic factors, confirming its predictive power. Our index captures important aspects of financial intermediation around the world.     

Why do exports react less to real exchange rate depreciations than to appreciations? Evidence from Pakistan

We examine if and why export responses to real exchange depreciations are lower than those to appreciations. We document this asymmetric response using macro-level data for Pakistan and show that export adjustments after depreciations are less than one-third as fast as those to appreciations. We use product-destination level data to examine three complementary drivers of this asymmetry: (i) information frictions that increase the search costs of finding new clients; (ii) supply constraints related limited access to credit that reduce exporters’ capacity to scale up after relative prices become more favorable; and (iii) reduced prices in US dollars offered by international buyers after local currency depreciations, akin to a pricing-to-market mechanism. We find evidence of the three drivers explaining the dampened export response to depreciations. Policymakers in developing countries should consider addressing these issues to maximize export responses to real depreciations.     

Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process

We consider a joint distribution that decomposes asset returns into two independent components: an elliptical innovation (Gaussian) and a systematic non-elliptical latent process. The paper provides a tractable approach to estimate the underlying parameters and, hence, the assets’ exposures to the latent non-elliptical factor. Additionally, the framework incorporates higher-order moments, such as skewness and kurtosis, for portfolio selection. Taking into account estimation risk, we investigate the economic contribution of the non-elliptical term. Overall, we find weak empirical evidence to support the inclusion of the non-elliptical term and, hence, the higher-order comoments. Nonetheless, our findings support the mean–variance (MV) decision rule that incorporates the elliptical term alone. Excluding the non-elliptical term results in more robust mean–variance estimates and, thus, enhanced out-of-sample performance. This evidence is significant among stocks that exhibit a strong deviation from the Gaussian property. Moreover, it is most pronounced during market turmoils, when exposures to the latent factor are highest.     

A random forest-based model for crypto asset forecasts in futures markets with out-of-sample prediction

In this study, a price prediction model for futures markets of crypto assets is presented. Random Forest was used to study three scenarios as a function of input variables: technical indicators, candlestick patterns and both simultaneously. In turn, the model parameters, the time intervals, and the most suitable investment horizons were studied. In addition to showing the results from the model, a one-year out-of-sample prediction was simulated. The entire year of 2020 was chosen because the three possible stock market scenarios occurred in this year: a sideways market, a bear market resulting from the global pandemic and an end-of-year bull market. Last, this out-of-sample simulation was analyzed as a real operation, that is, by retraining the model after each new collection of data, so that the model had the maximum information at all times. In conclusion, using candlestick patterns instead of technical indicators, improves the efficiency of the results.     

农户地租契约选择的经济逻辑:预期效用抑或损失规避

随着收入水平和社会保障水平的提高,农户的经济决策动机逐渐从风险(成本)最低转变为收益最大。但是,地租契约的不完全性等因素,可能使农户在选择地租契约时,需要在收益(租金)的可靠性和收益最大化之间进行权衡。文章理论分析表明,农户在选择地租契约时,其经济逻辑是损失规避而非预期效用理论。进而,文章利用中国家庭金融2015年调查数据,通过probit、IVprobit和似无相关回归模型检验了这一理论假说。研究结果显示,租金水平越高,农户越倾向于选择固定地租契约;消除内生性后的边际效应显示,租金提高每万元,农户选择固定租金契约的概率提高28.3%。机制分析发现,土地流转契约期限的增加会强化租金对农地转出户选择固定租金契约的影响。运用工具变量估计、交叉项和费舍尔组合检验三种方法进行稳健性检验后,该结论仍然成立。进一步的异质性分析结果表明,租金对固定地租契约的促进效应,在低收入农户中相对更高;在低收入农户中,契约期限不具有调节作用。研究结果为地租领域农户财产性收入的增加与政策预期的不一致,提供了理论解释与经验证据。基于此,文章提出为使农户通过地租获得更多的财产性收入,需要进一步完善农地流转契约治理机制等政策建议。     

Multivariate risk aversion utility,application to ESG investments

This paper uses the concept of multivariate or multi-attributive utility to attach different risk aversion levels to different sources of wealth (e.g. sectors, stocks, asset classes). In this context, we address the topic of environmental, social, and corporate governance (ESG) investments from the perspective of an investor with different risk aversion levels to green and brown stocks. We obtain closed-form solutions for the optimal allocations, value function, and wealth equivalent losses (WEL) from suboptimal choices. The numerical analysis demonstrates the significant increase, of up to 33%, in green investments when accounting for a differential in risk aversions levels, with up to 65% in WEL when using same risk-aversion levels.¹     

Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic

The Covid-19 pandemic played a relevant role in the diffusion of distance learning alternatives to “traditional” learning based on classroom activities, to allow university students to continue attending lessons during the most severe phases of the pandemic. In such a context, investigating the students' perspective on distance learning provides useful information to stakeholders to improve effective educational strategies, which could be useful also after the end of the emergency to favor the digital transformation in the higher educational setting.Here we focus on the satisfaction in distance learning for Italian university students. We rely on data comprising students enrolled in various Italian universities, which were inquired about several aspects related to learning distance.We explicitly take into account the hierarchical nature of data (i.e., students nested in universities) and the latent nature of the variable of interest (i.e., students' learning satisfaction) through a multilevel Item Response Theory model with students' and universities' covariates.As the main results of our study, we find out that distance learning satisfaction of students: (i) depends on the University where they study; (ii) is affected by some students' socio-demographic characteristics, among which psychological factors related to Covid-19; (iii) is affected by some observable university characteristics.