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Nowadays it is — to a certain extent — popular to criticize international tourism to third world countries. These criticisms may base on widely divergent aspects of the phenomenon, ranging from for instance the economic impact to the environmental impact or the psychological impact. Without implicitly suggesting that the non‐economic effects of international tourism in developing countries are unimportant we will concentrate in the following on the economic impact. The reason for this is twofold:

Estimates are developed of the major macroeconomic aggregates – wages, land rents, interest rates, prices, factor shares, sectoral shares in output and employment, and real wages – for England by decade between 1209 and 2008. The efficiency of the economy in the years 1209–2008 is also estimated. One finding is that the growth of real wages in the Industrial Revolution era and beyond was faster than the growth of output per person. Indeed until recently the greatest recipient of modern growth in England has been unskilled workers. The data also create a number of puzzles, the principal one being the very high levels of output and efficiency estimated for England in the medieval era. These data are thus inconsistent with the general notion that there was a period of Smithian growth between 1300 and 1800 which preceded the Industrial Revolution, as expressed in such recent works as De Vries (2008).

It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators.

To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis.

The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings.

These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate.

There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.

This paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties.

Among other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate.

Statistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth.

The findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development.

This study aims to explain the role of globalisation on the regional income growth disparities in the states of India and provinces in the People’s Republic of China (PRC).

The authors use two approaches to analyse regional growth disparities: growth accounting and the panel spatial Durbin model.

The growth accounting shows that contributions of growth of capital intensity (GKI) and total factor productivity growth (TFPG) distinguish the high-income (HI) regions from medium-income (MI) and lower-income (LI) regions in India. In the PRC, the contributions of GKI and TFPG in MI regions are slightly higher than HI regions, but significantly higher than the LI regions. The empirical results find that foreign direct investment (FDI), domestic investment, human capital, and interaction of FDI and human capital explain income growth states/provinces in India and the PRC. A region’s income growth and FDI inflows spread the benefit to neighbourhoods in both countries.

The paper contributes by performing a comparative analysis of Indian states and the PRC’s provinces by capturing the neighbourhood effects of economic growth, FDI, investment and human capital and also the interaction effects of FDI with human capital and domestic investment. A comparison of the decomposition of income growth to the growth of factor inputs and efficiency in Indian states and the PRC’s provinces also adds to the existing literature.

The demand for manpower resource by a hotel is derived from the public's demand for travel goods and services. In filling job vacancies, hotel managers are confronted with an array of internal constraints, industry‐specific drivers as well as external economy‐wide factors that influence the availability and cost of the labour input required. In this study a model incorporating relevant task and general environmental factors is used to measure their impact on hotel managers' decision to raise or lower the level of employment in hotels. Industry‐specific factors which were found to be statistically significant in influencing the demand for hotel staff included the number of hotel rooms, total revenue earned from room rentals and food and beverage sales and revenue obtained from the sale of these items. More broadly, general environmental factors of importance were the production index and the gross domestic product in impacting on the number of hotel employees hired by hotel management.

The purpose of this paper is to examine the export, import, and total trade determinants using reduced form equations for six Pacific Island countries (PICs) with an institutional focus.

A fixed effects model, controlling for AR(1) errors, using panel data for selected PICs is utilized. Controlling for common determinants of trade, four indicators of institutional quality: government effectiveness; rule of law; regulatory quality; and control of corruption are tested.

The empirical results indicate that improvements in institutional quality variables matter for improved levels of trade. The results also provide confirmation that the appreciation of currency does not significantly harm trade; higher levels of technological diffusion are vital for improved trade; and that gradual liberalization of trade through tariff reduction strongly facilitates more trade.

This study clearly points out that the institutional quality in the selected countries is a significant factor in determining the level of trade.

This paper expresses the view that institutions matter for enhanced trade.

This study aims to examine the relationship between economic growth and different indicators of air and water pollution in Malaysia. Air pollution indicators were assessed on a number of measures: carbon monoxide, sulphur dioxide (SO), nitrogen dioxide, ozone and particulate matter (PM) while water pollution indicators were evaluating on a number of measures: biochemical oxygen demand, cadmium and arsenic. The income level per capita gross domestic product per capita were measured from the year 1996 to 2006 quarterly. Being different from the study by Hung and Shaw (2004) and Shen (2006), this study estimates population density as an endogenous variable. It formulates a fourequation simultaneous model for empirical research. Testes for exogeneity with the Hausman test and estimates the simultaneity model using the two‐stages least squares method. The Environmental Kuznets Curve (EKC) hypothesis is supported in the cases of SO and PM, and there are several differences found between single polynomial equation estimators commonly used in EKC literatures and simultaneous equation estimators.

This paper aims to examine the impact of the components of human capital on the extent of poverty and income distribution in developing countries.

Data for all variables are from the World Development Report, 2006 and 2007. The least‐squares estimation technique in a multivariate linear regression is applied. It is noted that the introduction of interaction terms between income and the components of human capital yields better statistical results, as pointed out in the economic development literature.

Based on data from the World Bank and using a sample of 40 developing economies, it is found that the fraction of the population below the poverty line is linearly dependent upon gender parity ratio in primary and secondary schools, the prevalence of child malnutrition, per capita purchasing power parity gross national income, the maternal mortality rate, and the percentage of births attended by skilled health staff. Using another sample of 35 developing countries, it is found that income inequality linearly depends on the same explanatory variables plus the infant mortality rate and the primary school completion rate.

Statistical results of such empirical examination will assist governments in those countries identify areas that need to be improved upon in order to alleviate poverty and improve the distribution of income.

This paper provides useful information on the impact of the components of human capital on the extent of poverty and income distribution in developing countries.