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This paper aims to analyze the effectiveness of aid in stimulating investment using different measures of aid and up-to-date panel time-series techniques. This study controls for endogeneity by using dynamic ordinary least squares (DOLS) and minimizes the risk of running a spurious long-run relationship by using series that are cointegrated. This paper finds evidence that aid promotes investment in countries with good institutional quality and gain interesting insights on the influence of country characteristics and the amount of aid received. Aid is ineffective in countries with unfavorable country characteristics such as a colonial past, being landlocked and with large distances to markets. Aid can boost investment in regions that receive high (above-median) amounts of aid such as Africa and the Middle East but not in regions that receive low amounts of aid. Investment-targeted aid is effective but non-investment-related aid can also enhance investment.

Regressions on the aid-investment nexus are based on either a rather simple (115 countries) or an extended/augmented investment model (91 countries). The data covers the period of 1973–2011 and 1985–2011 if the institutional quality is included. This study estimates the relationship between aid and investment by applying the DOLS/dynamic feasible generalized least squares technique which is based on a long-run relationship of the regression variables (cointegration). In this framework, this paper incorporates country-fixed effects, control for endogeneity, autocorrelation and take heteroscedasticity and cross-country correlation of the residuals into account.

This study finds empirical evidence that aid promotes investment in countries with good institutional quality and gain interesting insights on the role played by country characteristics and the amount of aid received. Aid is ineffective in countries with unfavorable country characteristics such as the colonial past, being landlocked, distant from markets. Aid can boost investment in regions that receive high (above-median) amounts of aid such as Africa and the Middle East. Investment-targeted aid is effective but non-investment-related aid also able to enhance investment.

The study looks at the investment to gross domestic product (GDP) ratio (including domestic investment and foreign direct investment (FDI)) and, hence does not disentangle these factors. It looks at the net effect (positive and negative impact together) and, therefore does not allow to identify the direct crowding out the impact of aid. Of course, if this paper finds that aid has a negative impact on investment, it is clear that aid must have crowded out either domestic investment or FDI or both.

The authors think that it is relevant to have identified the circumstances and settings in which foreign aid can be particularly effective and in which foreign aid needs accompanying measures that improve the effectiveness of aid. Also, it is relevant that the relative amount of aid received (aid-to-GDP ratio) must be quite high so that aid can increase investment.

This study sees that the least developed, low-income countries and (in terms of regions) the sub-Saharan Africa countries benefit from aid. This is very desirable. This paper further sees that higher relative amounts of aid do help more and that it is helpful to care about a better institutional quality in developing countries. Hence, this study provides some support for the desirability of aid.

The paper was done very diligently, and this study is very confident that the results are robust. This paper is also confident that this study has studied the long-run (which is of special importance) nexus between aid and investment. The estimation technique used is original, as it combines regular DOLS with corrections for autocorrelation and cross-section dependence.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – FDI, remittances and official development assistance – can be a key factor in the development of the economy. The subject of this article is to analyses the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been employed. As part of this work, an attempt was made to use a panel data approach. The results indicate ambiguous effects and confirm the results of previous work.

The authors seek to study the effect of foreign direct investment, remittances and official development assistance (ODA) and some control variables i.e. domestic credit, life expectancy, gross fixed capital formation (GFCF), inflation and three institutional factors on economic growth in developing countries by adopting the panel data methodology. Then, the authors will discuss empirical tests to assess the econometric relevance of the model specification before presenting the analysis of the results and their interpretations that lead to economic policy implications. As part of this work, the authors have rolled panel data for developing countries at an annual frequency during the period from 1990 to 2016. In a first stage of empirical analysis, the authors will carry out a technical study of the heterogeneity test of the individual fixed effects of the countries. This kind of analysis makes it possible to identify the problems retained in the specific choice of econometric modeling to be undertaken in the specificities of the panel data.

The empirical results validate the hypotheses put forward and indicate the evidence of an ambiguous effect of financial flows on economic growth. The empirical findings from this analysis suggest the use of economic-type solutions to resolve some of the shortcomings encountered in terms of unexpected effects. Governments in these countries should improve the business environment by establishing a framework that further encourages domestic and foreign investment.

In this article, the authors adopt the panel data to study the links between financial flows and economic growth. The authors considered four groups of countries by income.

This paper analyzes the effects of the expiration of the Multi Fiber Arrangement (MFA), which ended quota restrictions on US textile and apparel imports in 2005, on the sourcing of US apparel. We test if the realignment in trade following the phase out of quotas can be explained by comparative advantage and market size.

We use a gravity framework to investigate the role of comparative advantage (labor costs) and other factors such as exporter size, PTAs and tariff reductions on the pattern of US apparel imports. Detailed data on quotas by country-product pair are used for the purpose.

Our empirical results show a significant increase in imports from large quota constrained countries once the MFA ended. Moreover, the pattern of trade seems to favor low wage countries that have a comparative advantage in producing apparel, which is highly labor intensive.

The end of quotas removed a major distorting factor in US apparel trade. This study examines the role of trade theory in the changing pattern of apparel imports that followed the end of the MFA. We use a gravity framework to test the theory of comparative advantage and the role of exporter size. Previous studies on the end of the MFA and its effects, do not examine the causal factors behind the realignment of US apparel trade.

This paper aims to revisit the relationship between intangible capital and labour productivity growth using the largest, up-to-date macro database (2000–2015) available to corroborate the econometric findings of earlier work and to generate novel econometric evidence by accounting for times of crisis (2008–2013) and economic recovery (2014–2015).

To achieve these aims, this paper employs a cross-country growth accounting econometric estimation approach using the largest, up-to-date database available encompassing 16 EU countries over the period 2000–2015. The paper accounts for times of crisis (2008–2013) and of economic recovery (2014–2015). It separately estimates the contribution of three distinct dimensions of intangible capital: (1) computerized information, (2) innovative property and (3) economic competencies.

First, when accounting for intangibles, the paper finds that these intangibles have become the dominant source of labour productivity growth in the EU, explaining up to 66 percent of growth. Second, when accounting for times of crisis (2008–2013), in contrast to tangible capital, the paper detects a solid positive relationship between intangibles and labour productivity growth. Third, when accounting for the economic recovery (2014–2015), the paper finds a highly significant and remarkably strong relationship between intangible capital and labour productivity growth.

This paper corroborates the importance of intangibles for labour productivity growth and thereby underlines the necessity to incorporate intangibles into today's national accounting frameworks in order to correctly depict the levels of capital investment being made in European economies. These levels are significantly higher than those currently reflected in the official statistics.