Human capital mobility patterns in the European Union and the financial crisis

This paper provides new evidence on the quantification of economic losses and/or gains from skilled human capital mobility in terms of GDP and productivity in several EU countries during and after the Great Recession. We construct two novel indicators to quantify and compare the economic effects of human capital mobility across EU countries in 2008, 2012, and 2016. Through hierarchical clustering, we created groups of countries to perform a non-parametric MANOVA. The results suggest the existence of three groups of countries aggregated by similar economic and mobility patterns. The differences between these groups are significant and allow us to delineate the countries’ gains and losses.

     

Efficient entrepreneurial culture: a cross-country analysis of developed countries

Entrepreneurship, together with national cultural values, may improve a country’s GDP levels. Under this hypothesis, the aim of this paper is to analyse the relationships between the levels of entrepreneurship, cultural values, and of GDP per capita in a sample of 27 developed countries, by identifying an efficient combination of culture and entrepreneurship variables, under the concept of efficient entrepreneurial culture, that maximises GDP per capita. Through the application of Data Envelopment Analysis (DEA) methodology, nine countries have been identified as having an efficient entrepreneurial culture. The implications derived for policy-makers are substantial, since a better understanding of cultural effects on entrepreneurship can lead to improvements in the design of governmental programmes that foster cultural values related to high-quality entrepreneurship.     

Purchasing power parity as a long-run relation

Dickey–Fuller and Stock–Watson tests of purchasing power parity (PPP) as a long-run proposition are provided within the cointegration framework proposed by Granger. Since different countries use different weights to construct price indices, the traditional constraint that the coefficients on the price indices should be unity in the log-linear PPP relation is relaxed. The absence of a general PPP relation cannot be rejected. At most, a PPP relation is indicated in five out of fifteen country pairs that are examined. Even if a long-run PPP relation exists, it is not found to be useful in predicting future nominal exchange rates, which is consistent with efficient speculative markets.     

A multilevel factor model: Identification,asymptotic theory and applications

This paper studies a multilevel factor model with global and country factors. The global factors affect all individuals, whereas the country factors affect only those within each specific country. A sequential procedure to identify the global and country factors separately is proposed. In the initial step, the global factors are estimated by canonical correlation analysis. Using this initial estimator, the principal component estimators (PCEs) of the global and country factors are constructed. It is shown that the PCEs estimate the spaces of the global and country factors consistently and are normally distributed in the limit. Several information criteria that can estimate the number of country factors are proposed. The number of global factors is assumed to be known. Extensive simulation results demonstrate that the sequential procedure and information criteria work well in finite samples. The method of this paper is applied to 25 OECD countries to identify an international business cycle. It is reported that the method extracts a global factor reasonably well.     

FORMAL AND INFORMAL SECTORS IN CHINA AND INDIA

This paper discusses the estimation of a social accounting matrix that distinguishes between formal and informal activities for China and India for 2000 and 1998–99 respectively. Wage shares for formal/informal employment in China and net domestic product shares for organized/unorganized sectors in India are used as weights to calculate the size of the two sectors. The proposed methodology is a first step towards an integrated approach to account for the dualism of many economies in the developing world. The results can serve as data input for any policy-driven CGE model for developing countries.     

Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.     

Optimal forecasts in the presence of structural breaks

This paper considers the problem of forecasting under continuous and discrete structural breaks and proposes weighting observations to obtain optimal forecasts in the MSFE sense. We derive optimal weights for one step ahead forecasts. Under continuous breaks, our approach largely recovers exponential smoothing weights. Under discrete breaks, we provide analytical expressions for optimal weights in models with a single regressor, and asymptotically valid weights for models with more than one regressor. It is shown that in these cases the optimal weight is the same across observations within a given regime and differs only across regimes. In practice, where information on structural breaks is uncertain, a forecasting procedure based on robust optimal weights is proposed. The relative performance of our proposed approach is investigated using Monte Carlo experiments and an empirical application to forecasting real GDP using the yield curve across nine industrial economies.     

Credit risk of subsidiaries of foreign banks in CEE countries: Impacts of the parent bank and home country economic environment

In this study, using dynamic panel data, we investigated the influences of the home country economic environment and parent bank condition on the credit risk of foreign banks in Central and Eastern European (CEE) countries. We concentrated on the international transmission of credit risk through the internal capital market of multinational banks. Our theoretical assumptions follow studies that document how the parent bank condition and home country macroeconomic environment affect lending in subsidiaries in CEE countries. However, our results go one step further. We provide evidence that these relationships are reflected in subsidiaries’ credit risk in CEE countries. Our results suggest that the size and profitability of the parent bank have negative influences, while the liquidity and credit risk of the parent bank have positive influences on the subsidiaries’ credit risk. Moreover, the GDP growth in the parent bank’s country has a negative effect on the credit risk of the subsidiary, while the lending rate and liquidity in the parent bank country cause growth in the credit risk. These results indicate a new channel of international risk transfer from parent bank countries to host countries through foreign-owned banks.     

Clustering eurozone cycles

Firstly, the study draws out symmetrical subsets of 27 member countries of the European Union (EU27) countries according to their extents of business cycle symmetry with the whole of EA12, quantified by correlations of cycles between the countries’ GDP components and the EA12s GDP. The objective is to evaluate the obtained country groupings against the EA12 countries, the initial members of the euro club. This exercise is implemented using hierarchical cluster analysis for pre- and post-euro periods. As a robustness check, a principal component analysis is applied. Secondly, the analysis deploys a discriminant technique on the cluster analysis solutions to identify the GDP component whose cycle synchronicity contributes most to separation of the countries. In a nutshell, the findings suggest a significant rise in fragmentation within EU27 and within EA12 after euroization and that cycle synchronization involving the GDP component of private investment as a more important determinant to country classifications.     

Determinants of total factor productivity in former Soviet Union economies: A stochastic frontier approach

This paper investigates the process of GDP generation in former Soviet Union (FSU) economies to provide an understanding of the impact of technology channels on countries’ efficiency. We apply a stochastic frontier approach to 15 FSU economies over the period 1995–2008 and find that FDI and human capital improve countries’ technical efficiency. Furthermore, we show that these factors also have a positive impact on total factor productivity (TFP), which, in turn, improves real GDP growth. Hence, our results suggest that FSU countries should promote public policies that provide incentives to attract foreign investment and enhance domestic education in order to improve their economic growth. Additionally, our empirical evidence argues against the resource curse hypothesis. We also show, by computing efficiency change and technological change indices at the country level, that FSU economies benefit more from exploiting technological progress than from catching up to the best practice frontier.     

Smoothing and Benchmarking for Small Area Estimation

Small area estimation is concerned with methodology for estimating population parameters associated with a geographic area defined by a cross-classification that may also include non-geographic dimensions. In this paper, we develop constrained estimation methods for small area problems: those requiring smoothness with respect to similarity across areas, such as geographic proximity or clustering by covariates, and benchmarking constraints, requiring weighted means of estimates to agree across levels of aggregation. We develop methods for constrained estimation decision theoretically and discuss their geometric interpretation. The constrained estimators are the solutions to tractable optimisation problems and have closed-form solutions. Mean squared errors of the constrained estimators are calculated via bootstrapping. Our approach assumes the Bayes estimator exists and is applicable to any proposed model. In addition, we give special cases of our techniques under certain distributional assumptions. We illustrate the proposed methodology using web-scraped data on Berlin rents aggregated over areas to ensure privacy.     

Growth in stress

We propose a new global risk index, Growth-in-Stress (GiS), that measures the expected fall in a country’s GDP as the global factors, which drive world growth, are subject to stressful conditions. Using the GDP growth rates of 87 countries, we find that, since the 2008 financial crisis, though mainly from 2011 on, the world overall has fallen in a state of complacency, with the cross-sectional average GiS falling quite dramatically; in 2015, the average worst outcome seems to be no growth at the 95% probability factor stress. However, the cross-sectional dispersion within groups is quite variable: it is the smallest among industrialized countries and the largest among emerging and developing countries. We also measure the factor stress on different quantiles of the GDP growth distribution of each country. We calculate an Armageddon-type event as we seek to find the GiS on the 5% quantile of growth under the extreme 95% probability events of the factors, and find that it can be as large as an annual 20% fall in GDP.     

GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul,Turkey

Fire stations play a central role in protection and response activities as part of emergency management services in cases of fire incidences. With the rising urban populations and city expansions, the demand for more fire services resultantly increases. It then becomes critical to effectively plan the location of emergency facilities to adequately service the population and ensure the protection of lives and infrastructure. This study, therefore proposes the use of the fuzzy extension of the Multi-Criteria Decision-Making (MCDM) method of Analytical Hierarchical Process (AHP), hence called fuzzy AHP, integrated with Geographic Information Systems (GIS) approach to optimally site new fire stations for the case of Istanbul region. This proposed fuzzy approach simulates the subjective expert judgements for the preferences of the six criteria assessed for fire station suitability mapping and thereby accounted for the uncertainty of crisp comparison values via triangular fuzzy numbers (TFNs). The criteria weights evaluated from this procedure were used in a weighted overlay analysis of the reclassified criteria map layers in ArcGIS to generate a fire station suitability map. These resultant fuzzy AHP criteria weights were validated using another MCDM technique, called Best-Worst Method (BWM) and found to be comparable and consistent. The criteria that had the strongest influence on the selection of sites for fire stations were identified to be: the density of hazardous material facilities (DHM), a high population density (HPD) and proximity to main roads (PMR) with associated weights of 33.3%, 24.4% and 15.2%, respectively. Based on a thorough assessment within the areas represented by class values ranging from 3 to 5 on the suitability map, a total of 34 new fire station sites were selected complementing the existing 121 fire stations. Further, a prioritization analysis from low, medium to high, was performed to plan the phases for the construction of new fire stations in view of competing budgetary needs and resource constraints. The methodology to achieve this was proposed and modelled for enhancing the decision-making process in urban fire station site selection studies.     

A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran

Human Development Index (HDI) is a useful tool for policy makers to understand the degree of development in their societies and set new policies to improve it. Traditionally, the United Nations Development Program (UNDP) releases HDI scores of countries based on the three key dimensions of healthy life, population education and standards of living annually. However, HDI scores have some deficiencies such as methodology, indexes selection and measures time lag. In this paper, a new approach is proposed to calculate semi-HDI scores. First, in each dimension of health, education and standard of living, new and extra criteria are selected. Then, policy makers' preferences are considered to assign the weights of criteria in each dimension using best worst method (BWM). Then, MULTIMOORA method is applied to rank provinces of Iran in each dimension. Finally, the semi-HDI scores of provinces are calculated based on geometric mean of healthy life, population education and living standards. According to the semi-HDI scores, Kohgiluyeh & Boyer- Ahmad and Sistan & Baluchestan provinces are the most and the least developed provinces of Iran, respectively.     

Economic sentiment and business cycles: A spillover methodology approach

This paper is one of the latest attempts to observe and explain the relationship between the Economic Sentiment Indicator (ESI) and GDP growth. This new approach uses the Diebold and Yilmaz (2012, 2009) spillover methodology by combining the feedback relationship and the time-varying (dynamic) aspect of that same relationship. The empirical analysis is based on quarterly data over different periods in the European Union (EU) (as a whole) and in ten Central and Eastern European (CEE) countries. The main results indicate that the spillovers of shocks between ESI and GDP growth are time-varying for all observed countries, with increasing values of total spillovers in the last recession and afterwards. The direction and strength of spillover effects between economic sentiment and GDP growth are different for the analysed CEE countries. The results are robust with respect to changing the rolling window length, additional Granger causality testing and rolling correlation coefficients.     

基于主客观决策信息一致化的组合赋权法

文章从客观的角度,提出一种综合主客观权重的组合权重确定法。该方法以主客观决策信息一致化为目标建立数学规划模型,通过求解该模型确定综合主客观权重的加权系数,并通过算例说明方法的有效性。     

An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe

In this study, an integrated multi-criteria framework is developed to evaluate a healthcare sector which is one of the main infrastructures for any country. Healthcare sector plays a significant role in economic development and social sustainability of countries. To improve performance of healthcare sectors, it is essentially required to evaluate the healthcare systems based on their specific characteristics in order to resolve their performance related issues based on sustainable development principles under social aspect. For this purpose, the proposed integrated framework applies a novel hybrid weight determination model using best-worst method (BWM) and level based weight assessment (LBWA) to determine the weights of healthcare indicators and subsequently, combined compromise solution (CoCoSo) method is further applied to evaluate healthcare performances of several countries according to the pre-determined indicator weights. To show applicability of the proposed framework, a real time case study for seven countries in Eastern Europe is considered based on the data set of Organisation for Economic Co-operation and Development (OECD). Results show that Lithuania and Slovakia have the best healthcare systems in comparison to countries like Poland and Estonia.     

A Welfare‐Based Approach to Aggregating Growth Rates across Countries*

Aggregating per capita gross domestic product growth across countries has always been a technical problem because of the complexities in the relative movements of exchange rates, economic output and populations. As such, the conventional approach to aggregating growth across countries suffers from sensitivity to exchange rates, as well as from the possibility of aggregate growth rates not being convex combinations of individual growth rates. This article introduces a new methodology in aggregating per capita growth rates that does not suffer from the drawbacks of the conventional approach. Using a welfare‐based approach, it is shown that the proposed methodology is robust w.r.t. exchange rates and generates weights that always add up to unity, thus avoiding the anomalies that are inherent in the conventional approach. The methodology proposed in the article is applied to calculate aggregate growth rates of 33 developing member countries as well as five regional groupings, and the results are compared with those arising from the conventional approach. A number of insights arise that were previously hidden or inaccessible.     

A SURVEY OF THE LITERATURE ON HUMAN CAPITAL‐INTENSIVE FIRMS

The aim of this paper is to provide an exhaustive survey of the academic research dedicated to the study of human capital‐intensive firms (HCIFs). We use a bibliometric analysis based on the three widely used databases (Econlit, Science Direct and Wiley) over the period 1992–2015. We are adapting a methodology developed in previous works to our specific object of study, and we generate a bottom‐up clustering on keywords, titles and abstracts. Our examination of the data sheds a light on five main clusters of works that respectively focus on (1) critical human resource management, (2) intellectual capital assessment, (3) funding risk and innovation (4) high‐skilled employees supporting economic development and (5) internal and external valuable social networks. In a critical appraisal of our results, we stress that the bibliometric analysis remains silent on how the different clusters are linked with each other. Based on our own appreciation of the HCIFs literature, we propose a further step in the identification of a central question linking up these clusters: a transversal review of the five clusters reveals that HCIFs appear as a network of specialized agents whose complementary human resources are decisive for the value‐creation process.     

Economies in Transition: How Important Is Trade Openness for Growth?*

We investigate the effect of trade openness on economic growth in transition countries using a transparent statistical methodology that leads to data‐driven case studies. In particular, we employ synthetic control methods in a panel of transition economies and compare GDP growth in treated (that is, open) countries with growth in a convex combination of similar but untreated (that is, closed) countries. We find that trade liberalization tends to have a positive effect on the pattern of real GDP per capita. One of our most robust results shows that making the transition without opening up to trade considerably hampers growth.