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The objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of digital technologies among European companies is studied through a composite index, while the relationship between innovation and AI is studied through a log-linear regression model. The results of the model have made possible to develop interesting indications for economic and industrial policy.

The use of digital technologies among European companies is studied through a composite index of AI and information technology (ICT) (using the Fair and Sustainable Welfare methodology) with the aim of measuring territorial gaps and to know which European countries are more or less inclined to its use, while the relationship between innovation and AI is studied through a log-linear regression model.

In the paper, two different methodologies were used to analyze the relationship between innovation and the development of digital technologies in Europe. The synthetic indicator made possible to develop a taxonomy between the different countries, the log-linear model made possible to identify and explain the determinants of innovation.

The description of the biunivocal relationship between innovation and AI is a topical and relevant issue that is treated in the paper in an original way using a synthetic indicator and a log-linear model.

本文旨在探討在歐洲、創新與人工智能和數字技術的發展之間的關係。研究人員透過一個綜合指數、去探討歐洲公司之間數字技術的使用狀況。至於創新與人工智能之間的關係, 則以對數線性回歸模型來進行研究。從模型所得的結果, 為我們提供了建議、去訂定適切的經濟和產業政策。

研究人員透過一個人工智能和資訊科技的綜合指數, 去探討歐洲企業之間數字技術的使用狀況 (研究人員使用了公平和可持續福利方法論), 其目標為測量領土差距, 以及確定哪些歐洲國家、大體上傾向於使用數字技術;至於創新與人工智能之間的關係, 則以對數性回歸模型來進行研究。

本文使用了兩個不同的方法、去探討在歐洲、創新與數字技術發展之間的關係。有關的合成指標, 使研究人員可製定一個不同國家間的分類法;而有關的對數線性模型, 則讓研究人員可確立並說明創新的決定因素。

本文使用了合成指標和對數線性模型、去探討創新與人工智能之間的一對一的關係, 這是時下受到關注和適宜的課題;就研究法而言, 本研究確是新穎獨創的。

The purpose of this study is to examine the relative importance of climate normals (average long-term temperature and precipitation) in explaining net farm revenue per hectare (NRh) for supplementary irrigated and rainfed cocoa farms in Nigeria.

NRh was estimated for 280 cocoa farmers sampled across seven Nigerian states. It was regressed on climate, household socio-economic characteristics and other control variables by using a Ricardian analytical framework. Marginal calculations were used to isolate the effects of climate change (CC) on cocoa farm revenues under supplementary irrigated and rainfed conditions. Future impacts of CC were simulated using Six CORDEX regional climate model (RCM) ensemble between 2036-2065 and 2071-2100.

Results indicate high sensitivity of NRh to Nigerian climate normals depending on whether farms use supplementary irrigation. Average annual temperature increases and precipitation decreases are associated with NRh losses for rainfed farms and gains for supplementary irrigated cocoa farms. Projections of future CC impacts suggest a wide range of NRh outcomes on supplementary irrigated and rainfed farm revenues, demonstrating the importance of irrigation as an effective adaptation strategy in Nigeria.

This paper uses novel data sets for simulating future CC impacts on land values in Nigeria. CORDEX data constitute the most comprehensive RCMs projections available for Africa.

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 study is to account for a recent non-mainstream econometric approach using microdata and how it can inform research in business administration. More specifically, the paper draws from the applied microeconometric literature stances in favor of fitting Poisson regression with robust standard errors rather than the OLS linear regression of a log-transformed dependent variable. In addition, the authors point to the appropriate Stata coding and take into account the possibility of failing to check for the existence of the estimates – convergency issues – as well as being sensitive to numerical problems.

The author details the main issues with the log-linear model, drawing from the applied econometric literature in favor of estimating multiplicative models for non-count data. Then, he provides the Stata commands and illustrates the differences in the coefficient and standard errors between both OLS and Poisson models using the health expenditure dataset from the RAND Health Insurance Experiment (RHIE).

The results indicate that the use of Poisson pseudo maximum likelihood estimators yield better results that the log-linear model, as well as other alternative models, such as Tobit and two-part models.

The originality of this study lies in demonstrating an alternative microeconometric technique to deal with positive skewness of dependent variables.

The study performs an empirical test to assess the impact of the Pakistan-China Free trade agreement (FTA) on Pakistan, China, and the World's exports under homogenous and differentiated products. This study employs the modeling with Poisson specification with Poisson Pseudo-Maximum Likelihood method for the estimations. The results of empirical test show that the effect of FTA on the FTA and Non-FTA countries is greater in the differentiated product as compared to the homogenous product. Therefore, one of the most important policy implications provided by this study is that export enterprises need to concentrate on differentiated products as compare to the homogenous products after the implementation of the Pakistan-China FTA. Moreover, the previous literature concluded that Pakistan-China FTA was more beneficial for China as compared to Pakistan. However, according to this study, if Pakistani enterprises focus more on differentiated products as compared to homogenous products, then it will be equally beneficial for both Chinese and Pakistani enterprises. This study will contribute to the literature by considering the Bertrand competition between asymmetric countries and find out the effect of the FTA on these three countries. It considers China, Pakistan, and the Rest of the World as first, second, and third countries.

The world over is becoming urbanized, and people are migrating to cities in large numbers in search of opportunities. The increased urbanization has posed challenges such as congestion, rising crime, and growing urban poverty. The governments respond by providing amenities such as schools, hospitals, and housing to meet to increase in demand for these facilities. However, there is a need for the provision of facilities that meets the expectations of the people, particularly on the proximity of amenities and bundles of utility-bearing housing characteristics. In an attempt to address the challenge mentioned, the study estimated the hedonic characteristics influencing the willingness to accept and willingness to pay for housing facilities in the Eastern Cape Province, South Africa. Using a multiple linear regression model and artificial neural network, the study found out that properties with a bathroom, garage and large floor size have a higher value compared to properties without these facilities.When making decisions to acquire a property, buyers consider the availability of discounts and the prevailing property price. Overall, willingness to pay and accept decisions are mainly determined by location and the price at which homogeneous neighborhood properties were sold. Therefore, the study recommends that urban town planners and other housing authorities prioritize the construction of properties with larger floor areas, parking bays, and bathrooms using a cost-effective mechanism that makes the properties affordable to residents.

The purpose of this study is to investigate long-run and short-run relationships between trade diversification, financial system development, capital formation and economic growth.

ARDL estimation approach is applied to analyze long-run and short-run relationships between the financial system development, capital formation, economic growth and trade diversification in case of the Sultanate of Oman over the period 39 years starting from 1979 till 2017.

The results show that financial system development and economic growth has a positive impact on trade diversification in the short-run and long-run. However, capital formation has a negative impact on trade diversification in the short run and long run. The negative relationship between trade diversification and capital formation implies that over the period of study, the investment in capital goods was made to enhance the production capacity of the oil sector to maximize revenue.

This research is limited to analyze long-run and short-run relationship between the financial system development, capital formation and economic growth and trade diversification in case of Sultanate of Oman.

To achieve the diversification goal, the policymakers need to formulate policies to strengthen the financial system and invest in infrastructure development to promote the non-oil sector. The research findings of this study will provide insights to the policymakers to formulate an effective diversification policy.

This research contributes to the existing literature by providing empirical evidence of the short-run and long-run analysis of the selected variables in the context of an oil-dependent country.

This paper analyzes the issue of wage differentials and gender discrimination in the Brazilian labor market.

The methodology is based on the log-linear equation model by Mincer (1974) and the decomposition method by Oaxaca (1973) and Blinder (1973) and was estimated using data from the National Household Sample Survey (PNAD).

The main results indicate that there was a reduction in wage differentials and gender discrimination in the majority of regions in Brazil for white workers when comparing the available years. However, for non-white workers, the degree of discrimination increased in Brazil, especially in the central-west and southeast regions. Overall, wage decompositions have suggested that women suffer from wage discrimination.

This is the first paper detailing wage discrimination across the different Brazilian regions and also controlling for usual dimensions like gender and race.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2021-0569.

While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions.

A literature survey.

While there are many useful applications of SFA to econometrics, there are also many important open problems.

This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.

This study proposes spatial origin-destination threshold Tobit to address spatial interdependence among bilateral trade flows while accounting for zero trade volumes.

This model is designed to capture multiple forms of spatial autocorrelation embedded in “directional” trade flows. The authors apply this improved model to export flows among 32 Asian countries in 1990.

The empirical results indicate the presence of all three types of spatial dependence: exporter-based, importer-based and exporter-to-importer-based. After further considering multifaceted spatial correlation in bilateral trade flows, the authors find that the effect of conventional trade variables changes in a noticeable way.

This finding implies that the standard gravity model may produce biased estimates if it does not take spatial dependence into account.

This paper attempts to offer an improved model of the standard gravity model by taking spatial dependence into account.