scholarly journals Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

Author(s):  
Matías Mayor ◽  
Roberto Patuelli
2019 ◽  
Vol 41 (1) ◽  
pp. 68-83 ◽  
Author(s):  
Claudio Quintano ◽  
Paolo Mazzocchi ◽  
Antonella Rocca

Purpose The purpose of this paper is to understand: whether the changes that have occurred in migrants’ conditions over time are smaller than the differences in their conditions existing across countries; and whether the comparison between immigrants and native-born conditions allows the verification of the levels of disparities between them and, therefore, the relative disadvantage suffered by migrant. After a general overview of the 28 European Union countries, this paper analyses the changes that have occurred from 2006 to 2017 in the conditions of migrants in the labour market in the big five European countries (Italy, Spain, France, Germany and the UK). Design/methodology/approach Various statistical methodologies were used. First, to gain an overall picture, taking into account both the spatial and the temporal dimensions, dynamic factor analysis (DFA) was applied. Second, time-dependent and cross-sectional time-series models were estimated to better understand the DFA results. Findings The results highlight very different scenarios in terms of labour market vulnerabilities, both affecting immigrants and native-born workers. The results also highlight the existence of a very complex framework, due to the high heterogeneity of immigrants’ characteristics and labour market capacities to integrate migrants and also to promote good conditions for the native-born population. Originality/value The picture emerging from this study and the evaluation of the policies and legislation in force to cope with migration and to promote integration suggests some reflections on the most efficacious actions to take in order to improve migrants’ integration, counteracting social exclusion and promoting economic growth.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nahla Samargandi ◽  
Kazi Sohag ◽  
Ali Kutan ◽  
Maha Alandejani

PurposeThe authors reinforce the existing literature on the effect of overall globalization on institutional quality (IQ), while incorporating the effects of economic, political and social aspects of globalization, human capital, government expenditure and population growth. To this end, the authors estimate panel data models for a sample of 36 member countries of the Organization of Islamic Cooperation (OIC) during 1984–2016.Design/methodology/approachThe authors employ the cross-sectional autoregressive distributed lags (CS-ARDL) approach.FindingsThe study’s investigation affirms the presence of an inverted U-shaped (nonlinear) relation between overall globalization and IQ indexes for the sample countries, which suggests no additional room for improvement in IQ. It also underpins the existence of an inverted-U-shaped (nonlinear) relation between political globalization and IQ. In contrast, economic and social globalizations have a U-shaped relation with IQ, implying more scope for improvement.Research limitations/implicationsThe findings have key policy implications. First, policy makers should consider a long-run approach for improving IQ and globalization over time. Second, quick reforms in the short run may not improve IQ.Practical implicationsThe results suggest that policy makers should approach the globalization process from a long-run perspective as well by designing appropriate strategies to provide a continuous but gradual increase in globalization so as to systematically monitor the threshold limits to IQ from improving globalizationOriginality/valueTo the best of the authors’ knowledge, this work is the first to empirically investigate the overall role of globalization in promoting IQ under the conditions of short-run heterogeneity and long-run homogeneity. The authors focus on the member countries of the OIC, many of which are ruled by authoritarian regimes and suffer from a poor domestic institutional setting.


2016 ◽  
Vol 5 (1) ◽  
pp. 73-81 ◽  
Author(s):  
Nicholas Apergis ◽  
James E Payne

Purpose – The purpose of this paper is to extend the existing literature on the causal dynamics between entrepreneurship and the unemployment rate (UR) in the use of the Kauffman Foundation index of entrepreneurial activity. Design/methodology/approach – Recently developed panel unit root tests with recognition of cross-sectional dependence and panel cointegration/error correction modeling techniques are applied to US States. Findings – The results indicate that the rate of entrepreneurship, the UR, and real per capita personal income are cointegrated. The panel error correction model reveals that bidirectional causality exists among the variables in both the short run and long run. With respect to entrepreneurship, an increase in the UR increases the rate of entrepreneurship, in turn, an increase in the rate of entrepreneurship lowers the UR. Moreover, the results also show a positive bidirectional relationship between the rate of entrepreneurship and real per capita personal income. Originality/value – Unlike other standard measures of entrepreneurship, this is the first empirical study of the causal dynamics between entrepreneurship and the UR using the Kauffman Foundation index of entrepreneurial activity.


2010 ◽  
Vol 2 (2) ◽  
pp. 194-214
Author(s):  
Polasek Wolfgang ◽  
Carlos Llano ◽  
Richard Sellner

Chow and Lin (1971) were the first to develop a unified framework for the three problems(interpolation, extrapolation and distribution) of predicting times series by related series(the ‘indicators’). This paper develops a spatial Chow-Lin procedure for cross-sectional data and compares the classical and Bayesian estimation methods. We outline the error covariance structure in a spatial context and derive the BLUE for ML and Bayesian MCMC estimation. In an example, we apply the procedure to Spanish regional GDP data between2000 and 2004. We assume that only NUTS-2 GDP is known and predict GDP at NUTS-3level by using socio-economic and spatial information available at NUTS-3. The spatial neighbourhood is defined by either km distance, travel time, contiguity or trade relationships. After running some sensitivity analysis, we present the forecast accuracy criteria comparing the predicted values with the observed ones.


2018 ◽  
pp. 46-67 ◽  
Author(s):  
Matheus Koengkan ◽  
Luciano Dias Losekann ◽  
José Alberto Fuinhas ◽  
António Cardoso Marques

This article analyses the impact of hydroelectricity consumption on environmental degradation (CO2 emissions) in seven South American countries, in a period from 1966 to 2015. The Unrestricted Error Correction Model (UECM) form of the Auto-regressive Distributive Lag (ARDL) was utilized. The initial tests prove the presence of heteroskedasticity, cross sectional independence, and first-order autocorrelation. The results show that the consumption of hydroelectricity causes a reduction of -0.0465 in environmental degradation in the short run, and increase 0.0593 in the long-run. This empirical evidence could encourage the creation of new policies, which introduce new energy technologies that release zero carbon in the energy matrix.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yann Ferrat ◽  
Frédéric Daty ◽  
Radu Burlacu

PurposeThe growth of socially responsible assets has been exponential over the last decade, they now account for almost a third of professional investments. As the growth persists, faith and conviction investors reshape the equity markets. To fully comprehend the impact of socially conscious participants on security returns, this paper attempts to provide insights on how responsible investment growth has impacted the returns of sustainable stocks. The examination is split by investment horizon to account for short and long effects.Design/methodology/approachUsing an exclusive dataset of non-financial ratings, provided by MSCI ESG research, the authors examine the cross-sectional returns of US and European sustainability-leading and lagging corporations between 2007 and 2019. Panel models robust to country, firm-year and industry effects were then employed to examine the impact of responsible investment growth on future stock returns.FindingsThe authors find evidence that the impact of responsible investment growth is dual contingent upon the timeframe considered. In the short run, sustainability-leading and lagging firms display similar stock returns. However, the spread in returns is negative over long horizons and increasing over time.Originality/valueThe examination performed in this study highlights the significant effect of responsible investment growth on future stock returns. Overall, the authors’ findings are consistent with the price pressure hypothesis in the short run and the cost of capital alteration over longer horizons.


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