Thresholds in the Finance-Growth Nexus: A Cross-Country Analysis

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Thresholds in the Finance-Growth Nexus: A Cross-Country Analysis

One sentence summary: Finance accelerates economic growth when inflation is below 8%.

The corresponding paper by Hakan Yilmazkuday has been published at World Bank Economic Review.

The paper is available here.


Abstract

Thresholds of inflation, government size, trade openness, and per capita income for the finance-growth nexus are investigated using five-year averages of standard variables for 84 countries from 1965 to 2004. The results suggest that (i) high inflation crowds out positive effects of financial depth on long-run growth, (ii) small government sizes hurt the finance-growth nexus in low-income countries, while large government sizes hurt high-income countries, (iii) low levels of trade openness are sufficient for finance-growth nexus in high-income countries, but low-income countries need higher levels of trade openness for similar magnitudes of the finance-growth nexus, (iv) catch-up effects through the finance-growth nexus are higher for moderate per capita income levels.

Non-technical Summary

The benefits obtained by individuals from eliminating the whole macroeconomic instability in a given economy are almost certain to be negligibly small, when compared with those that can be obtained with more growth.  Therefore, even the global financial crisis that has started at the end of 2007, considered to be the biggest one since the Great Depression by most economists, should not matter from a welfare analysis point of view, and countries, especially the developing ones, should still focus on the long-run growth. In this context, the impact of financial development on the long-run growth is of particular interest: A healthy financial system not only encourages savings, but also improves the allocation of such savings to efficient investment projects; this, in turn, encourages an efficient and high level of capital formation to promote growth. However, what are the necessary economic conditions and/or environments to achieve such a healthy finance-growth nexus? Does high inflation lead financial depth to show its negative impacts on growth or does it only eliminate the positive effects? Is there any optimal level of trade openness or government size for the development of finance-growth nexus in low-income and high-income countries? Who benefits most from the catch-up (convergence) effects through the finance-growth nexus? Is the finance-growth nexus stable through time? All these questions are sought to be answered here by investigating the historical experiences of 84 countries from 1965 to 2004 and considering the nonlinearities in the finance-growth nexus through a continuous threshold analysis.

The effect of inflation on growth is found to be negative, especially in the literature on empirical growth. This is attributed to increasing uncertainties, mostly because of increasing relative price variability, increasing difficulties in planning, or increasing expectations of disinflation. This study finds that high inflation crowds out the positive effects of financial depth on long-run growth; however, the threshold inflation rate estimated by this study is about 8 percent, independent of the financial-depth measure used.

The government expenditure can promote growth through the provision of public goods, such as property rights, national defense, legal system, and police protection; however, large public expenditures would tend to crowd out potentially productive private investments. The empirical evidence is in line with this claim suggesting that the effects of government size on growth are mixed. In the context of the finance-growth nexus, this study shows that small government sizes hurt low-income countries (e.g., owing to the lack of sufficient public goods, such as infrastructure or property rights, to have an effective financial system), while large government sizes hurt high-income countries (e.g., owing to the crowding-out effect described earlier); thus, the optimal government size, on an average, is found to be between 11 and 19 percent.

Trade openness can endorse growth through providing access to large and high-income markets, together with low-cost intermediate inputs and technologies; however, it can also lead to more vulnerability through international shocks (either trade or finance). Such effects of trade openness on growth have been studied extensively. Although relatively recent works assign an important role for trade openness in economic growth, considerable skepticism does exist about this relationship. On the contrary, low-income countries need higher levels of trade openness for similar magnitudes of finance-growth nexus, because they can benefit from larger, high-technology and high-income markets only through high levels of openness.

The argument that low-income countries can grow faster than high-income countries has been studied extensively. The so-called "catch-up effect" is due to the low costs of industrialization in low-income countries through imitating already-developed technologies in high-income countries. This story can be connected to the neoclassical theory of diminishing returns to physical capital, which should cause more advanced countries to grow more slowly than the less advanced countries. However, in empirical terms, the evidence is mixed. As financial development is costly and difficult, one would expect  that catch-up effects would start manifesting only after the income crosses a certain threshold value. Considering all possible income levels, this study shows that the catch-up effect, through the finance-growth nexus, does not start until a country reaches the threshold per capita income level of about $665 (in constant 1995 U.S. dollars), and that it would not work effectively until that income level reaches about $1,636 (in constant 1995 U.S. dollars).

Overall, this research paper has generalized the empirical studies on the finance-growth nexus by considering the thresholds in several explanatory variables. Following are the suggestions that emerged from this study: (i) Inflation rates above 8 percent eliminate the positive effects of financial depth on the long-run growth. (ii) Optimal government size (% GDP) for the finance-growth nexus is between 11 and 19 percent; government sizes below 11 percent hurt the low-income countries, and those above 19 percent hurt the high-income countries. (iii) Optimal trade openness for the finance-growth nexus is below about 35 percent for high-income countries, and above about 75 percent for low-income countries. (iv) The catch-up effect through finance-growth nexus starts when a country passes the threshold per capita income level of about $665; it has its highest impact when the per capita income is about $1,636; its impact decreases as the per capita income increases. (v) There is evidence to show that financial-depth effects on growth decrease through time.  (vi) The thresholds in the initial per capita income seem to be more important than other thresholds.

Agglomeration and Trade: State-Level Evidence from U.S. Industries

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Agglomeration and Trade: State-Level Evidence from U.S. Industries

One sentence summary: Industry- and state-level international exports and intermediate input trade within the U.S. are systematically connected to production agglomeration and specialization effects.

The corresponding paper by Hakan Yilmazkuday has been published at Journal of Regional Science.

The working paper version is available here.

Abstract

This paper investigates the connection between economic agglomeration and trade patterns within the U.S. at the industry level. On the consumption side, industry- and state-specific international imports and elasticities of substitution are shown to be systematically connected to consumption agglomeration effects, while on the production side, industry- and state-specific international exports and intermediate input trade are shown to be systematically connected to production agglomeration and specialization effects. Industry structures play an important role in the determination and magnitude of these effects.

Non-technical Summary

According to the United States (U.S.) trade data, intranational trade volume is more than 6 times international trade volume, on average, between 1993 and 2007. This paper sheds light on this difference by introducing a regional trade model that connects international and intranational trade patterns to the distributions of production and consumption within the U.S.. The investigation can be categorized under two topics:

1. On the production side, what portion of the state- and industry-level production is consumed as a final good within the U.S., and what portion of it is used as an intermediate input within the U.S. or exported to other countries? How are these portions connected to economic agglomeration and specialization effects?
2. On the consumption side, what are the elasticities of substitution across products of different states at the state and industry levels? Are these elasticities systematically connected to economic agglomeration and specialization effects? Do these elasticities have further implications for the shares of consumption (at the state and industry levels) imported from other countries; are these shares systematically connected to economic agglomeration and specialization effects?

The model consists of individuals and firms in a discrete framework where there are finite number of goods and regions. There are two types of goods, namely traded and non-traded. Each region produces non-traded goods together with a variety of each traded good. Traded goods can be traded up to a transportation cost, and each region may consume varieties of each traded good besides non-traded goods. Production of traded goods is achieved by only labor, while the production of non-traded goods requires traded goods. Thus, traded goods can be used either as a final good or an intermediate input in the model. Individuals in each region have different elasticities of substitution across varieties of each traded good. This, in turn, leads optimization of each monopolistically competitive firm resulting in prices equal to marginal costs with region/good specific mark-ups. According to the model, the main motivation behind trade is found to be the heterogeneity across regions/goods in terms of factor costs, production technologies, transportation technologies, locations, and taste parameters.

Non-traded goods are consumed only locally by definition. So, only the traded goods are modelled in this paper although the existence of non-traded goods, through their intermediate input usage, is considered explicitly. After carefully controlling for intermediate input trade and international trade, the remaining part, the final good trade, is analyzed extensively. In particular, the model is numerically solved using the available data to figure out the region/good specific elasticities of substitution and portions of production that are used as final goods within the country. After that, possible economic connections between international imports, elasticities of substitution, and consumption patterns, as well as connections between international exports, intermediate input trade, and production patterns, are investigated through agglomeration and specialization of the industries at the state level.

Instead of using trade flow data, which do not have sufficient information about the exact distribution (e.g., agglomeration, specialization) and structure (e.g., technology, marginal costs) of production and consumption across regions, the consumption, production, and trade implications of a partial equilibrium model are tested using industry-specific production and consumption data at the state level. In particular, four state-level industry data are considered within the U.S.: 1) Food and beverage and tobacco products, 2) Apparel and leather and allied products, 3) Computer and electronic products, and 4) Furniture and related products.

On the consumption side, it is shown that the industry- and state-level elasticities of substitution can be significantly explained by consumption agglomerations; the elasticities are positively (respectively, negatively) affected by agglomeration of consumption for food and furniture (respectively, for apparel and electronics). The differences across these industries are connected to the homogeneity of the products, where homogeneity is further supported by numerically calculated median elasticities of substitution across states/industries. Consumption agglomerations are also connected to international imports at the industry and state levels.

On the production side, it is shown that the industry- and state-level portion of production that is used as a final good within the country can be significantly explained by both agglomeration and specialization of the industries; these portions are negatively related to both effects. In other words, the industry- and state-level portion of production that is used as an intermediate input or exported abroad is significantly and positively related to agglomeration and specialization of the industries across states. Thus, agglomeration and specialization of industries play an important role in determining the patterns of trade, both intranationally and internationally. Finally, comparisons across industries suggest that the spillover effects are much higher for electronics compared to food, apparel, or furniture, in terms of both consumption and production. High explanatory powers in the regression analyses further support the model.