Commodity Price Volatility and Inclusive Growth in Low-Income Countries
Chapter

Chapter 8. What Is Inclusive Growth?

Author(s):
Rabah Arezki, Catherine Pattillo, Marc Quintyn, and Min Zhu
Published Date:
October 2012
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Author(s)
Elena Ianchovichina and Susanna Lundstrom Gablee 

Introduction

The purpose of this chapter is to define the meaning of the term “inclusive growth.” It is often used interchangeably with a suite of other terms, including “broad-based growth,” “shared growth,” and “pro-poor growth.” Many times it is unclear what people have in mind when they define growth as inclusive and how this type of growth relates to the widely discussed extensive and intensive growth patterns.

We clarify the distinctions and similarities between these related terms and outline the defining characteristics of inclusive growth (IG); we also argue that IG analytics has a distinct character focusing on both the pace and pattern of growth. Traditionally, poverty and growth analyses have been conducted separately. In this chapter, we describe the conceptual elements for an analytical strategy aimed at integrating these two strands of analysis and to identify and prioritize the country-specific constraints to sustained and inclusive growth.

Defining Inclusive Growth

Rapid and sustained poverty reduction requires IG that allows people to contribute to and benefit from economic growth.1 Rapid pace of growth is unquestionably necessary for substantial poverty reduction, but for this growth to be sustainable in the long term, it should be broad-based across sectors2 and inclusive of a large part of the country’s labor force.3 This definition of IG further emphasizes the importance of both extensive and intensive growth. Rapid pace of growth and employment can be achieved through extensive growth, which requires expansion of the quantity of inputs, but for this type of growth to be sustainable in the long term and for employment to be productive, there must be periods when growth is intensive and occurs because of productivity improvements, technological breakthroughs, and other innovations rather than capacity expansion.

This definition of IG implies also a direct link between the macroeconomic and microeconomic dimensions of growth. The macroeconomic dimension is in line with the vast literature, which relies on Solow-Swan-type balanced growth models (Solow, 1956; Swan, 1956) and typically disregards the dramatic sectoral reallocation of labor experienced by fast-growing economies.4 The micro-economic dimension captures the importance of structural transformation for economic diversification and competition, including creative destruction of jobs and firms. The reallocation process, often called “structural change,” has been documented by researchers such as Kuznets (1957) and Chenery (1960), but this literature ignores the Kaldor properties related to balanced growth. A more recent paper by Kongsamut, Rebelo, and Xie (2001) brings together these two strands of the literature by putting forward a theoretical model consistent with balanced growth and the dynamics of sectoral labor reallocation.

IG refers to both the pace and pattern of growth, which are considered to be interlinked and therefore need to be addressed together. The idea that both the pace and pattern of growth are critical for achieving a high, sustainable growth record, as well as poverty reduction, is consistent with the findings in The Growth Report: Strategies for Sustained Growth and Inclusive Development (Commission on Growth and Development, 2008). This report notes that inclusiveness—a concept that encompasses equity, equality of opportunity, and protection in market and employment transitions—is an essential ingredient of any successful growth strategy. Here we emphasize the idea of equality of opportunity in terms of access to markets, resources, and unbiased regulatory environment for businesses and individuals.5 The Commission on Growth and Development (2008) considers systematic inequality of opportunity “toxic,” as it will derail the growth process through political channels or conflict.

The IG approach takes a longer-term perspective, as the focus is on productive employment rather than on direct income redistribution as a means of increasing incomes for excluded groups. In the short term, governments could potentially use income distribution schemes to attenuate negative impacts on the poor of policies intended to jump-start growth, which may be relevant for a number of reasons in a specific country context. However, the IG approach includes the analysis of inclusion through productive employment as transfer schemes cannot be an answer in the long term and can be problematic also in the short term.6 In poor countries, such schemes can impose significant burdens on already stretched budgets, and it is theoretically impossible to reduce poverty through redistribution in countries where average income falls below US$700 per year. According to a recent OECD study, even in developed countries, redistribution schemes cannot be the only response to rising poverty rates in certain segments of the population (OECD, 2008).

The IG definition is in line with the absolute definition of pro-poor growth, but not the relative definition. Under the absolute definition, growth is considered to be pro-poor as long as poor people benefit in absolute terms, as reflected in some agreed measures of poverty (Ravallion and Chen, 2003). In contrast, under the relative definition, growth is pro-poor if and only if the incomes of poor people grow faster than those of the population as a whole; that is, inequality declines. However, while absolute pro-poor growth can be the result of direct income redistribution schemes, for growth to be inclusive, productivity must be improved and new employment opportunities created. In short, IG is about raising the pace of growth and enlarging the size of the economy, while leveling the playing field for investment and increasing productive employment opportunities.

By focusing on inequality, the relative definition could lead to suboptimal outcomes for both poor and non-poor households. For example, a society attempting to achieve pro-poor growth under the relative definition would favor an outcome characterized by average income growth of 2 percent in which the income of poor households grew by 3 percent over an outcome in which average growth was 6 percent, but the incomes of poor households grew by only 4 percent. Although the distributional pattern of growth favors poor households in the first scenario, both poor and non-poor households are better off in the second scenario. There is broad recognition that when poverty reduction is the objective, then the absolute definition of pro-poor growth is the most relevant (DfID, 2004). Under the absolute definition, the aim is to increase the rate of growth to achieve the greatest pace of poverty reduction.

IG analysis focuses on sources of and constraints to sustained high growth, and not only on one group, that is, the poor. The analysis looks at ways to raise the pace of growth by using more fully the parts of the labor force trapped in low-productivity activities or those completely excluded from the growth process. This is in contrast to the pro-poor growth literature, which has traditionally focused on measuring the impact of growth on poverty reduction by tracking various poverty measures. Box 8.1 summarizes the discussion and the key features of IG.

Box 8.1What Is Inclusive Growth About?

1. Inclusive growth (IG) focuses on economic growth, which is a necessary and crucial condition for poverty reduction.

2. IG adopts a long-term perspective and is concerned both with the pace and pattern of growth. High pace of growth is important, but how growth is generated is critical for growth sustainability and for accelerating employment creation and poverty reduction.

  • Rapid pace of growth and employment can be achieved through extensive growth, which requires expansion of capacity, but for this type of growth to be sustainable and for employment to be productive, there must be periods when growth is intensive and accompanied by productivity improvements and innovation.

  • For growth to be sustainable in the long term, it should be broad-based across sectors. Issues of structural transformation for economic diversification therefore take front stage. However, some countries may be an exception and continue to specialize as they develop due to their specific conditions (e.g., small states).

  • It should also be inclusive of the large part of the country’s labor force, where inclusiveness refers to equality of opportunity in terms of access to markets, resources, and unbiased regulatory environment for businesses and individuals

3. IG strategies must be tailored to country-specific circumstances.

4. IG focuses on productive employment rather than income redistribution. Hence, the focus is not only on employment growth, but also on productivity growth.

5. IG focuses not only on the firm, but also on the individual as the subject of analysis.

6. IG is in line with the absolute definition of pro-poor growth, not the relative one.

7. IG is not defined in terms of specific targets such as employment generation or income distribution. These are potential outcomes, not specific goals.

8. IG is typically fueled by market-driven sources of growth, with the government playing a facilitating role.

Policies for IG are an important component of most government strategies for sustainable growth. For instance, a country that has grown rapidly over a decade but has not seen substantial reduction in poverty rates may need to focus specifically on the inclusiveness of its growth strategy, that is, on the equality of opportunity for individuals and firms (see, e.g., Ianchovichina and Lundstrom, 2009). Other examples can be drawn from resource-rich countries. Extractive industries usually do not employ much labor, and the nonresource sectors typically suffer contractions associated with Dutch disease effects during boom periods. These cases may call for analysis of constraints to broad-based growth with a particular emphasis on the nonresource sectors in the economy (one such case is presented in Ianchovichina and Gooptu, 2007). Moreover, in countries starting at a very low income level and low growth, an IG approach would be very close to an approach for speeding up the pace of growth, as the main focus should be on getting the fundamentals for growth right.

What Does the Literature Tell US?

The report of the Commission on Growth and Development (2008) reviewed 13 cases of high sustained growth in the postwar period.7 Four of the thirteen countries are the newly industrialized countries in East Asia—Hong Kong Special Administrative Region (China), Republic of Korea, Singapore, and Taiwan Province of China. Young (1995) showed the fundamental role played by factor accumulation in explaining the extraordinary postwar growth of these four economies. Participation rates, education levels, and investment rates rose rapidly in all four economies in the postwar period. Once Young (1995) accounted for the steep rise in factor inputs, he found estimated TFP growth rates that were comparable to the historical TFP growth rates in OECD and Latin American economies. He concluded that the unprecedented growth in the newly industrialized countries was associated with unprecedented extensive growth rather than unprecedented intensive growth. This finding underscored the view that a successful IG strategy must have both extensive and intensive growth components and that the mix between these two varies across countries and time periods.

A high pace of growth over extended periods of time is a necessary and often the main contributing factor in reducing poverty, as found by a sizable body of literature, including Deininger and Squire (1998), Dollar and Kraay (2002), White and Anderson (2001), Ravallion (2001), and Bourguignon (2003). In a frequently cited cross-country study, Kraay (2004) shows that growth in average incomes explains 70 percent of the variation in poverty reduction (as measured by the headcount ratio) in the short term and as much as 97 percent in the long term. Most of the remainder of the variation in poverty reduction is accounted for by changes in the distribution, with only a negligible share attributed to differences in the growth elasticity of poverty. Lopez and Servén (2004) suggested that for a given inequality level, the poorer the country is, the more important is the growth component in explaining poverty reduction.

Sustained high growth rates and poverty reduction, however, can be realized only when the sources of growth are expanding, and an increasing share of the labor force is included in the growth process in an efficient way. This process is typically accompanied by the massive reallocation of labor from agriculture into manufacturing and services in a process called structural change and labor productivity changes. Duarte and Restuccia (2010) found that productivity catch-up in industry explains 50 percent of the gains in aggregate productivity across countries, whereas low productivity in services and the lack of catch-up explain all experiences of growth slowdowns and stagnation.

From a static point of view, growth associated with progressive distributional changes will have a greater impact in reducing poverty than growth that leaves distribution unchanged. Evidence in White and Anderson (2001) suggests that in a significant number of cases (around one-quarter), distribution has been as important as growth in explaining the income growth of the poor.8

Some policies may have a positive effect on both growth and inequality. The empirical cross-country literature suggests that growth has neither a positive nor a negative effect on inequality (see Deininger and Squire, 1996; Ravallion and Chen, 1997; Easterly, 1999; and Dollar and Kraay, 2002) and that the impact of inequality on growth is ambiguous.9 These results do not imply the absence of links when looking at a specific policy or a specific country. Lopez (2004b) surveyed the empirical literature and concluded that macroeconomic stability related to inflation, as well as education and infrastructure-related policies, seem to be win-win or “super pro-poor” policies that have both a positive effect on growth and a negative effect on inequality.

Moreover, asset inequality rather than income inequality may matter for growth outcomes. Deininger and Squire (1998) used land distribution as a proxy for asset inequality and showed that high asset inequality has a significant negative effect on growth. Controlling for initial asset inequality, Birdsall and Londono (1997) showed that income inequality does not seem to play a role in expanding growth outcomes.

The cross-country literature on both growth and pro-poor growth has been criticized for not giving enough guidance to policymakers. Much of the pro-poor growth agenda has been focusing on aggregated income and poverty statistics, measuring to what extent growth has been poverty reducing and analyzing whether and why poverty was reduced in an absolute or relative sense.

In the early 2000s, however, a new wave of literature emerged focusing on the importance of the context and ex ante analysis of constraints to future economic development.10 Several cross-country studies have shown that growth determinants are highly dependent on initial conditions such as levels of income, poverty, and asset inequality, but also a host of other factors such as geography, demography, governance, politics, social considerations, and the set of existing policies. These differ not only between countries, but also over time within the same country.

One key example of the post-1990s literature is the volume Economic Growth in the 1990s: Learning from a Decade of Reform (World Bank, 2005). It concludes that although the necessary fundamentals for growth, such as a stable macroeconomic environment, enforcement of property rights, openness to trade, and effective government, are key factors in the growth process, they are not the whole story. This work and the work of the Commission on Growth and Development (2008) highlight the diverse ways in which the fundamentals can interact with policies and institutional setups in different country contexts.

An important insight from this stream of research is that numerous distortions exist at any time in a given country and that some are more important than others. Moreover, as posited in the theory of the second best, it can actually be welfare reducing to institute reforms that remove some distortions as long as other distortions remain, which is the case in all real economies.11

Targeting the distortion associated with the biggest multiplier,12 and therefore the largest direct welfare impact, is a good alternative because the second-best effects are typically hard to estimate with accuracy. Other options include targeting all distortions at once (a strategy sometimes associated with the Washington Consensus approach), which is often an infeasible option due to financial and capacity constraints, especially in low-income countries. But targeting the biggest distortion or a number of distortions may not lead to a welfare improvement because of the possibility of large second-best effects.

It is against this background that Hausmann, Rodrik, and Velasco (2005) developed a heuristic approach to identifying the most binding constraint to growth, that is, the one with the largest shadow price so as to increase the chance of a positive welfare effect. They use a decision tree framework based on the Euler equation or Keynes-Ramsey rule, which captures many of the most important factors affecting growth of an economy in the short term:13

and holds in the case of balanced growth equilibrium. In this equation, c is consumption per capita; k is capital per worker, a is technological progress; θ is an index of externality; x is availability of complementary factors of production, such as infrastructure or human capital; τ is the tax rate; ρ = z + n is the real interest rate; n is population growth; z is the rate of time preference; and σ is the inverse of the negative of the elasticity of marginal utility. If the cost of capital ρ is high for any return on investment, investment is low and the economy is considered to be “liquidity constrained.” If the rate of return r is low, for any cost of capital, investment is low and the economy is “considered inefficient.”14

There are important lessons to be learned from this approach, including that development policy is country specific and may involve just a few reforms that can be optimally sequenced to relax binding constraints, leading to large positive welfare impacts. However, finding the binding constraints requires careful thinking. Some of the criticisms of this approach emphasize that (1) it is impossible to estimate shadow prices in practice, (2) it is very difficult to reject constraints as not binding, and (3) the analysis is focused on the short term and therefore ignores factors important to sustainable growth such as human capital accumulation.

The analysis has also been undertaken at an aggregate level, offering little insight about constraints affecting different sectors, types of firms, or the obstacles to economic transformation in the long term. And as argued, economic transformation is fundamental for sustained, broad-based growth because it allows economies to catch up and sustain high growth rates over extended periods of time (Romer, 1990; Aghion and Howitt, 1992; Aghion and others, 2005; Duarte and Restuccia, 2010). Empirical evidence shows that not a single country has been able to achieve significant income growth and poverty reduction without structural transformation and economic diversification (Imbs and Wacziarg, 2003). For low-income countries and countries with small domestic markets, structural transformation entails export diversification as access to foreign markets enables countries to realize economies of scale (Hausmann, Hwang, and Rodrik, 2007).

It is important to point out that structural transformation is a necessary but not a sufficient condition for growth sustainability, especially in those cases in which it is achieved with the help of government subsidies and other interventions and the new industries are unable to compete without them. In addition, some countries may continue to specialize as they grow due to their specific circumstances, such as their small size.

Finally, the Hausmann, Rodrik, and Velasco framework also abstracts from conditions affecting the ability of individuals to engage productively and contribute to economic transformation. It includes human capital as a likely constraint from the perspective of firms, but does not look at whether skills limit the ability of certain economic actors—be they the poor, residents of a specific region, or women or other excluded groups—to engage in economic development and the constraints limiting investment in human capital.

The Inclusive Growth Approach

The framework is just one among many approaches to IG analytics. It is particularly relevant in cases where income level, growth, and investments are low. Against this background, the Hausmann, Rodrik, and Velasco framework is an appropriate framework for studying issues of IG since growth is the main driver of poverty reduction. In cases in which growth is concentrated in a few sectors or specific types of economic actors, the framework should be modified and supplemented with analysis of constraints to growth in the slow-growing and emerging sectors and constraints to individuals to contribute and benefit from growth. The appropriate framework will depend on country- and time-specific factors.

In cases in which growth is high but poverty reduction stagnates, the analysis could be carried out using an IG analytics framework15 (Ianchovichina and Lundstrom, 2009) that is eclectic in spirit. It blends the diagnostic approach with different techniques applied to time series, firm, and household survey data and cross-country benchmark comparisons to answer questions about trends, constraints to, and sources of sustainable, broad-based growth. The economic agent in an IG analytics framework is the individual rather than the firm, but individuals employed in firms earn returns to their employment, either as self- or wage-employed. The analysis does not need to be limited to the poor, but could be conducted from the perspective of different groups in the labor force, such as people living in a lagging region, migrants, or women. If one defines the income of any individual i as

where wj and Ej are the prices and endowments of each of the economy’s j factors and ωij is the share of the jth factor owned by individual i. Then, dividing each side by total income and summing over the poor individuals, one obtains

where ψP is the share of income received by the poor, λj is the share of factor i in total income, and ωPj is the share of factor j owned by the poor. This identity indicates the variables that affect the income share of the poor.

The main instrument for a sustainable and inclusive growth is assumed to be productive employment.16 Employment growth generates new jobs and income for the individual—from wages in all types of firms or from self-employment, usually in micro firms—while productivity growth has the potential to lift the wages of those employed and the returns to the self-employed. After all, in many low-income countries, the problem is not unemployment, but rather underemployment. Hence, IG is not only about employment growth, but also about productivity growth, that is, not only about extensive growth, but also about intensive growth. In other words, there is no preconception or bias in favor of labor-intensive industry policies. Indeed, the self-employed poor need improvements in productivity and leveling of the business environment to raise their incomes and to allow family members, for instance, to leave family farms and get employment elsewhere. So the analysis covers not only wage- employment, but also self-employment, which means that returns to capital, land, and other assets matter in regard to the income potential of the focus group as shown in the identity above.

The ability of individuals to be productively employed depends on the opportunities to make full use of available resources as the economy evolves over time. The IG analysis, therefore, tries to identify ways to strengthen the productive resources and capacity of the individual on the labor supply side as well as ways to open up new opportunities for productive employment on the labor demand side.

If the main problem is lack of employment opportunities for a particular group of individuals due to limited supply of certain types of labor skills, the constraints are related to the productive resources and capacity of individuals rather than the environment in which they can use these resources. This situation calls for an in-depth employability analysis that will shed light on the resources of the individuals, such as the individuals’ education and health and the other productivity attributes they bring to a job. If the main problem is low labor productivity or lack of employment opportunities for the individuals due to limited demand for labor, an analysis of the bottlenecks in the business environment is necessary (the Hausmann, Rodrik, and Velasco approach being one example).

The analysis distinguishes between self- or wage-employed and further looks at employment by sector, size of firm, rural/urban, formal/informal, and other relevant characteristics. A disaggregated look is necessitated by our main objective to identify the incidence of growth across the income distribution and the bottlenecks to the productive employment of individuals. If the focus is on the poor, in the case of the self-employed, we undertake business environment analysis through the lenses of the small enterprises and micro firms. In the case of the wage-employed, we undertake an employability analysis as well as a business environment analysis through the lenses of a representative firm, potentially one that is employing the poor.17

An important question is the extent to which the current employment status of an individual has a potential for future income growth, or if moving out of a low-income situation means finding another type of employment or employment in another sector. The analysis therefore looks at external factors explaining the country’s growth and poverty reduction pattern, the overall productivity dynamics in the country, the major challenges and opportunities, and possibilities for economic transformation and diversification. The analysis also considers constraints to those sectors with opportunities for productive employment, constraints affecting the ability to gain employment in these sectors, and constraints affecting labor mobility across sectors and regions.

The IG approach takes a longer-term perspective. This is necessary because of the emphasis on improving the productive capacity of individuals and creating a conducive environment for employment rather than on income redistribution as a means of increasing incomes for excluded groups. Due to this longer-term perspective, there is an explicit focus on structural transformation and internal migration in the IG analytics framework. In developing countries, a significant part of growth is generated through reallocation of labor from low-productivity to high-productivity sectors (Duarte and Restuccia, 2010).

With this longer-term perspective, it is important to recognize the time lag between reforms and outcomes. A good example is the lag between the time when investments in education are made and the time when returns from improved labor skills are collected. This implies that the analysis must identify future constraints to growth that may not be binding today, but that may need to be addressed today in order to ensure sustainable and inclusive growth. In short, IG analytics is about policies that should be implemented in the short term but for sustainable IG in the future. The goal is to identify a bundle of binding constraints rather than the binding constraint and then sequence these constraints to enhance prospects for high, sustained IG in a country over a period of time.18

Concluding Remarks

In this chapter, we have defined the meaning of IG and presented the argument that a focus on IG has a distinct character emphasizing both the pace and pattern of growth. Rapid pace of growth is unquestionably necessary for substantial poverty reduction, but for this growth to be sustainable in the long term, it should be increasingly broad based across sectors and inclusive of the large part of the country’s labor force. This definition of IG emphasizes the importance of both extensive and intensive growth and implies a direct link between the macroeconomic and microeconomic determinants of growth and captures the importance of structural transformation for economic diversification and competition.

IG is about raising the pace of growth and enlarging the size of the economy, while leveling the playing field for investment and increasing productive employment opportunities. It focuses on ex ante analysis of sources of and constraints to sustained high growth, and not only on one group; that is, the poor. The analysis looks for ways to raise the pace of growth by more fully using parts of the labor force trapped in low-productivity activities or completely excluded from the growth process.

Policies for IG are an important component of any government strategy for sustainable growth, and the frameworks for IG analytics are eclectic in spirit. The main instrument for a sustainable and inclusive growth is assumed to be productive employment. Employment growth generates new jobs and income for the individual—from wages in all types of firms, or from self-employment, usually in microfirms, whereas productivity growth has the potential to lift the wages of those employed and the returns to the self-employed. The ability of individuals to be productively employed depends on the opportunities to make full use of available resources as the economy evolves over time. The analysis therefore looks at ways to strengthen the productive resources and capacity of the individual on the labor supply side as well as ways to open up new opportunities for productive employment on the labor demand side.

The IG approach takes a longer-term perspective. With this longer-term perspective, it is important to recognize the time lag between reforms and outcomes. IG analytics is about policies that should be implemented in the short term but for sustainable IG in the future.

References

We would like to thank Carlos Braga, Leonardo Garrido, Vandana Chandra, Loga Gnanasambanthan, Lili Liu, Rabah Arezki, Harry Hagan, Fernando Hernandez, Eduardo Ley, Elina Scheja, Juan Pedro Schmid, and the donors to the Diagnostics Facility for Shared Growth for their useful comments on earlier drafts.

This statement is in line with the OECD Development Assistance Committee’s policy statement on pro-poor growth. However, a difference between pro-poor and inclusive growth is that the pro-poor approach is mainly interested in the welfare of the poor, whereas inclusive growth is concerned with opportunities for the majority of the labor force, poor and middle class alike.

Imbs and Wacziarg (2003) showed that countries diversify as they develop. Countries start specializing quite late in the development process, and the turnaround point occurs at a robust level of income per capita (around constant 1985 US$10,000). They conclude that increased sectoral specialization applies only to high-income economies. It is important to note that some countries may not broaden their economic base as they develop due to their specific economic conditions (e.g., small states).

Encouraging broad-based and inclusive growth does not imply a return to government-sponsored industrial policies, but instead puts the emphasis on policies that remove constraints to growth and create a level playing field for investment.

Romer (1986) and Lucas (1988) introduced endogenous growth models that reflected the critical role of human capital, innovation, and knowledge spillovers for economic growth but preserved their balanced growth properties.

According to the report of the Commission on Growth and Development, a persistent, determined focus on inclusive long-term growth by governments is one of the ingredients of a successful growth strategy. Yet there is limited analytic work integrating the literature on growth and productive employment.

The term “shared growth” can be misunderstood as implying a focus on income distribution schemes, which is why “inclusive growth” is preferred.

These 13 cases were Botswana, Brazil, China, Hong Kong Special Administrative Region (China), Indonesia, Japan, Malaysia, Malta, Oman, Republic of Korea, Singapore, Taiwan Province of China, and Thailand.

White and Anderson (2001) constructed the data set using the Deininger and Squire database. They identified 143 growth episodes in all, of which about half are from developing countries. Coverage of Africa was weak, with only Zambia appearing from sub-Saharan Africa. Data for the countries of the former Soviet Union and eastern Europe were only up to the 1980s, thus predating the large increases in inequality that took place in the early 1990s.

Alesina and Rodrik (1994) and Alesina and Perotti (1996) found a negative relationship, Li and Zhou (1998) and Forbes (2000) found a positive relationship, and Barro (2000) and Lopez (2004a) found no relationship.

Analyses of sources of growth, such as growth decomposition and poverty decomposition, are important to our understanding of country-specific context and past sources of growth.

In formal terms, duldτi=λi+Σjλj(μjsμjp)/τi, where u is welfare, τi is a distortion in activityi, λi is the Lagrange multiplier corresponding to the constraint associated with the distortion in activity i, μis represents the net marginal valuations of activity i by society s, and μip by private agents. The direct effect is always welfare improving, but the indirect effect may not be, implying a possibility that welfare may decline if the indirect effect is negative and larger than the direct effect.

The distortion associated with the biggest multiplier effect is the binding constraint.

This is the Hamiltonian for the simplest Ramsey-type optimal growth model, which assumes that households have perfect foresight and need to decide how much labor and capital to rent to firms and how much to save or consume by maximizing their individual utility subject to their budget constraint. Firms maximize profits at each point in time and produce a single good. In their production function, technology is exogenous and so are the complementary factors of production and the index of externality. The government spending requirements are assumed to be fixed exogenously; the government imposes a tax on the rental price of capital, so the after-tax return to capital is r(1 –τ).

The cost of finance ρ may be high because the country has limited access to external capital markets or because of problems in the domestic financial market. A country may have difficulties accessing external capital markets for a variety of reasons including high country risk, unattractive FDI conditions, vulnerabilities in the debt maturity structure, and excessive regulations of the capital account. Bad local finance may be due to low domestic saving, poor domestic financial intermediation, or both. Return to capital r may be low due to insufficient investment in complementary factors of production, such as infrastructure and human capital, low land productivity due to poor natural resource management, or low private returns to capital due to high taxes, poor property rights, corruption, labor-capital conflicts, macro instability, and market failures, such as coordination externalities and learning externalities negatively affecting the country’s ability to adopt new technologies.

This framework was inspired by the framework of the “Integrated Economic Analysis for Pro-Poor Growth” (Sida, 2006).

According to the Commission on Growth and Development report (2008), sustained high growth requires rapid incremental productive employment.

Note that the analysis of labor skills as a potential constraint for the self-employed is captured in the business environment analysis where it is analyzed as a constraint to growth of the small firm.

This does not mean we go back to the “laundry list” approach, but rather to a limited set of constraints. Sequencing of these constraints, however, may require further in-depth studies of the feasibility and costs of specific policies.

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