Evaluating Projections of African Economic Growth

A discussion of the African Development Bank’s report utilizing the Solow Model and examining welfare effects.



GDP per capita in Sub-Saharan Africa is the lowest in the world at $1,594 in 2015 (World Bank 2015). Rates of extreme poverty (living on less than $1.90 per person per day) are the highest in the world at 40 percent in 2015 (World Bank 2015). While other countries such as China, India, Vietnam and Cambodia have experienced rapid growth over the last quarter century, bringing millions of their citizens out of poverty and industrializing their economies, most African countries have economies based largely on agriculture and commodities, sectors that are susceptible to shifts in exogenous factors such as international prices and weather. As the continent seeks to alleviate the mass poverty, build its vital infrastructure, and join the ranks of other high-growth countries, the African Development Bank (AfDB) was instituted to “spur sustainable economic development and social progress in its regional member countries (RMCs), thus contributing to poverty reduction” (AfDB).

The AfDB recently held its 52nd annual meeting, at which it released its annual assessment on the economic outlook for Africa. A newspaper article in the Ugandan Daily Monitor, “Africa’s Economic Growth Bright – AfDB,” reported on the document and summarized its projections. The report predicted growth of 3.4 percent in 2017, up from 2.2 percent in 2016. The lower growth in 2016 was “due to low commodity prices, weak global recovery and adverse weather conditions” and the expected rebound in 2017 is “on the assumption that as commodity prices recover, the world economy will be strengthened and domestic macroeconomic reforms are entrenched” (Daily Monitor, June 2017).

Are the Report’s Assumptions Realistic?

The growth rates predicted in the AfDB’s report are higher than growth rates in the United States. This is not surprising, as developing countries typically have higher growth rates than developed countries. While higher than projected growth rates in developed countries, the AfDB report’s rates are lower than those projected in China. China’s growth rate, although slowing somewhat (from 14 percent in 2012 to 7 percent in 2015), remains one of the highest in the world. That the projection in the AFDB report is between that of the United States’ and China seems reasonable.

Although the figure might be within a reasonable range, it is important to evaluate if the assumptions made about the drivers of this growth are reasonable. The projection is based “on the assumption that as commodity prices recover, the world economy will be strengthened and domestic macroeconomic reforms are entrenched.”

The assumption that commodity prices will go up is line with most analysts’ estimates. The World Bank’s Commodity Markets Outlook forecasts higher prices for industrial commodities such as energies and metal and stable prices or a small decrease in the prices of grains and some other agricultural products (World Bank, April 2017). As different African countries contain different natural resources and have varying economic dependence on commodity exports, they will be affected individually by price changes. But the overall impact of price changes is likely to be positive.

It is a strong assumption to say that the world economy will be strengthened next year. There is a great deal of uncertainty in international trade and financial markets being caused by international terrorism and the nationalistic movements in the Europe and the United States. Furthermore, the continued cooling of China’s economy will not only affect international growth, but also will significantly reduce demand for raw materials. This will have a severe impact on Africa, as many African countries’ economies are reliant on exports of raw materials.

Finally, the reinforcement of domestic macroeconomic reforms within Africa depends on African leaders’ willingness to fight corruption and make their markets better for doing business. The incentives align for these reforms to advance and Africa’s economy should continue to become more pro-growth. So, while some of the assumptions in the AfDB’s report are more realistic than others, it is safe to expect economic conditions that are favorable for growth in Africa.

Evaluating African Growth Using Economic Models

Economists use formalized models to derive predictions about future economic growth within one country and differences in growth patterns among countries. One such macroeconomic model is the Solow Model, named after Robert M. Solow, who won the Nobel Prize in Economics for the 1956 paper in which he introduced the model (Solow 1956). It is a neoclassical model in that total output is a function of capital and labor. The model expresses output in per worker terms such that per capita GDP only grows with capital accumulation, which in turn only increases by a higher saving rate or lower rate of depreciation of capital. The implication is that a higher saving rate increases per-capita GDP, but that the growth rate of per capita GDP would return to zero. Later revisions to the Solow model added in a term for human capital to explain sustained economic growth and differences in cross-country differences in per-capita GDP (Mankiw et al, 1992).

Unfortunately, the Solow Model is not particularly suitable for evaluating the drivers of growth that are projected in the AfDB report. Higher commodity prices are essentially lump-sum payments to commodity exporting countries. While this is going to make those countries better off, changes in the terms of trade do not have an impact on the Solow Model output function or growth rate function. Similarly, a strong recovery in the global economy does not directly factor into the Solow Model. However, these sources of growth will have an indirect effect on the Solow Model output function. A stronger global recovery will give multinational corporations additional capital to invest, higher commodity prices will direct that capital towards commodity-rich countries, and African domestic macroeconomic reforms will encourage these corporations that Africa is business-friendly. This increase in foreign direct investment raises the level of capital. Per the Solow Model, this will lead to a higher level of output and a higher level of growth in the short-term. These results are consistent with the AfDB’s report.

Welfare Implications

            Assuming the projections within the AfDB’s report are accurate, how will this growth impact poverty, inequality and other measures of household well-being? Because the growth is mainly projected to be driven by changes in commodity prices, demand for the unskilled labor that produces these commodities will increase and the remote areas where these resources are located will gain greater access to domestic and international markets. These changes will reduce poverty and improve the standards of living among the rural poor in African countries. Nonetheless, the clear majority of the income that will arise from the increase in commodity prices will likely flow to wealthier portions of the population who provide the capital to produce these commodities. As such, the effect of the growth on measures of inequality such as the Gini Coefficient is unclear.



“Africas economic growth bright – AfDB.” Daily Monitor. Nation Media Group, 01 June 2017. Web. 06 June 2017.


“Industrial Commodity Prices to Rise in 2017.” World Bank. World Bank Group, 26 Apr. 2017. Web. 07 June 2017.


Mankiw, N. Gregory, et al. “A Contribution to the Empirics of Economic Growth.” The Quarterly Journal of Economics, vol. 107, no. 2, 1992, pp. 407–437. JSTOR, www.jstor.org/stable/2118477


“Mission & Strategy.” African Development Bank. N.p., n.d. Web. 06 June 2017.


Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) http://data.worldbank.org/indicator/SI.POV.DDAY?locations=ZG&view=chart


Solow, Robert M. “A Contribution to the Theory of Economic Growth.” The Quarterly Journal of Economics, vol. 70, no. 1, 1956, pp. 65–94. JSTOR, www.jstor.org/stable/1884513.


Growing Indian Agriculture by Leaving Farmers Alone

The Economic Times of India published an article titled “Need policies to ensure farmers get better prices: Arvind Panagariya” last week. Though the article itself is relatively short, it fits into a broader policy debate that is being held in the Indian government. Namely, there has been a lot of discussion recently about whether to tax rural farmers, and if so, how much. The Indian central government does not have the constitutional authority to levy taxes on agriculture, so the debate is focused on a state by state basis, where taxing agriculture is allowed.

The Context

The National Institution for Transforming India (NITI Aayog), the leading think-tank in India, and India’s prime minister, Narendra Modi, have stated a goal of doubling agriculture income in India by 2022. Supporting technology adoption and ensuring competitive prices domestically and internationally are the main intended methods to achieve this growth. While India’s economy has developed significantly in recent years, its poorest citizens are still largely living in an undeveloped economy. According to Arvind Panagariya, “80% of the poor… in rural areas are dependent on farming.” In addition, it appears that most farmers in India rely on agriculture for subsistence.

NITI Aayog leaders and the prime minister have been asked about taxation of agriculture income in India. Almost unanimously, policy leaders have stated that there is not even a question of taxing agriculture income. However, most reports do not give a complete picture to the phrasing of “no question” when it comes to taxing farmers. Do they mean that it is obvious a provision will be included to tax farmers in the future, or that it is obviously a bad idea to tax subsistence farmers and the rural poor.

In a separate report, the Chief Economic Advisor, Arvind Subramanian, suggested that taxation of agriculture income is possible. He added, policymakers must make a distinction between rich and poor farmers.

The Model

Luckily, there are clear models that address production and wealth gains over time. Depending on the structure of the tax, a farmer would consider it as a fixed cost or a variable cost in their production function. In a developing economy, we must also realize that any money a farmer has to pay to the government cannot be used to re-invest in their farm, either as better inputs or durable goods. When analyzing this issue, it is important to make the same distinction that Mr. Subramanian did. Wealthier farmers, or those who have commercialized and see yearly profits, have much more flexibility to be taxed.

Unless state governments face strains, taxing all farmers would make the poorest and subsistence farmers much worse off, since their year on year gains in wealth and potential reinvestment would be undercut. In general, taxing farmers as their income increases from subsistence to commercial would reduce productivity and would be counterproductive to alleviating poverty.

On the most basic level, taxing subsistence farming would push the poorest farmers into a worse position, and would not encourage adoption of new inputs and technologies. In order to commercialize and take advantage of the government’s push to raise prices for agriculture products, poor farmers need access to new technology. We discussed the incentives farmers face when adopting new technologies; they must be educated and the benefits must outweigh the costs.

These policymakers are correct in their belief that taxing agriculture should be out of the question. By taxing agriculture, subsistence and poor farmers face a greater cost or diminished benefit to their yearly yields. In the face of uncertainty, they will be less likely to experiment with new technologies and will not have the resources to try new crops and inputs. The agricultural technology adoption model shows farmers each running experiments over time is the best way to increase their output. By limiting the resources for experimentation, agricultural growth will be significantly slowed, and this effect will compound over time.

Another factor of the agricultural technology adoption model at play in this decision is “information neighbors”. The policymakers aim to increase the prices of crops. In order for their ultimate goal to be achieved, doubling rural income by 2022, the first phase must be giving farmers the means to adopt new technologies. However, the real gains in production are compounded over time as farmers experiment and communicate with their neighbors.


If India’s policymakers are serious about increasing agriculture productivity and income, then taxation is absolutely “no question”. In a country like the United States, where industrial agriculture is the norm, taxation is possible because of the surplus that farmers face. However, in India’s case most farmers need to be nudged into commercialized agriculture and educated about the new technologies available. In order to achieve this, the whole system should be tailored toward the goal. Also, based on NITI Aayog’s statistics, increasing rural income can benefit a huge portion of the impoverished population in India as well. Based on these facts, Indian policymakers have made the right decision for ensuring growth of agriculture output.



Sources Cited:







When There Is Not Enough Credit to Go Around: The Challenges of Accessing Microcredit in Myanmar

As financial regulations lax and with the entrance of more nongovernmental organizations into Myanmar, microfinance and the availability of microloans have made it much easier for citizens of Myanmar to gain access to credit that they would not otherwise have access to. However, the demand for credit is far greater than the current supply. Currently, over 2.8 million clients have access to microloans in Myanmar. As that number continues to grow, credit constraints, the lack of credit availability, and the lack of financial literacy has made it difficult for people who need credit the most to access it. (The World Bank)

An article from the Myanmar Times published on March 1, 2017, Agricultural Sector and SMEs to Receive Private Bank Loans, talks about recent policy changes implemented to help farmers and small business owners. With the intervention of the Myanmar Private Sector Development Committee (PSDC), the committee has passed into law that private banks in Myanmar must grant a minimum percentage of all their commercial loans to people in the agricultural or SMEs (Micro, small, and medium-sized enterprises) sectors (Htwe.)

The current Agricultural Minister of Myanmar, Myint Hlaing, has stated, “The agricultural sector is the backbone of Myanmar’s economy as the entire agricultural sector contributes 30% of its current GDP. In addition, 61% of the country’s labor force is working in the agricultural sector” (Centre for Agriculture and Bioscience International.) Since agriculture is such a large part of the Myanmar economy, it is understood that additional funding and capital is required for the industry and economy to develop.

As of now, microloans are only made by state-owned banks. Local private banks rarely lend to local borrowers because of the lack of profitability and high risks of lending. Many of the private citizens who require microloans do not have the collateral nor credit history to justify receiving a loan, and laws set by the government cap the amount of interest that private banks can charge on these private loans (13%.)

(The World Bank)

The state-run banks currently charge an 8.5% interest rate and an 8% interest rate to SMEs and farmers, respectively. Should a borrower go to a private bank, they would be charged a 13% interest rate. Currently, it is unfeasible for private banks to
match the interest rate of the state-run bank, as they pay 8% interest rates on banking deposits (Htwe.) The main issue here, is deciding upon interest rate that would satisfy the state-run bank, the privately-owned bank, and the borrower.

With the passing of the 2016 Monetary Law, banks are no longer required to collect collateral when deciding who to give loans out to, but that just makes the vetting process more difficult. Despite the law, many private banks still require collateral as they cannot thoroughly vet borrowers, and many banking relationships in Myanmar are built on trust and reputation (Htwe.)
U Thein Myint, a deputy general manager at one of Myanmar’s privately-owned banks argues that, “If people fail to pay back their loans, the banks will encounter difficulties in paying deposits from its customers. This is detrimental to the financial system and the national economy. Therefore, for people seeking bank loans, they need to provide strong guarantee.” Until there is a proven high chance that commercial banks will be paid back, loans provided for the agricultural and SMEs sectors will remain low (Htwe.)

A retired vice president of the Myanmar Central Bank, U Than Lwin, hopes that the government can work out an arrangement with private banks so that money can be lent to people who need it the most. A proposed idea would be for the government to implement a system so that they can partially guarantee loan repayment, which would make the lending process for banks much easier. Another idea would be to mitigate risk by lending to a larger group of people, by spreading the amount of risk that people would take on when taking out a loan.

Some of the issues described in the article written by Chan Mya Htwe regarding microcredit are also issues seen in countries struggling to meet the demand for microcredit by their citizens. This is amongst one of the many challenges encountered for governments or NGOs implementing a microcredit and microfinance program in a developing country (Schaffner.) In a country where access to finance is difficult and people are spread out across rural areas, there is adverse selection on both sides for both the borrower and lender. Lending caps and inconsistent lending practices make it hard for borrowers to access loans. This usually results in a loan from multiple financial institutions or a loan shark (Schaffner.) The inconsistent income that depends on the planting and growing season along with the lack of good jobs makes it difficult in certain cases, for people to pay back their loans. With the new law instituted by the government preventing banks from collecting collateral on loans, the end result is an inefficient outcome where the borrower does not get the money they need for their everyday life and the lender just makes loans elsewhere where the financial institution knows they will be paid back.

Private financial institutions need a new way to thoroughly vet prospective borrowers if they cannot collect collateral beforehand (Htwe.) There is a possibility of lending to large groups and spreading out risk through group liability, but in every borrowing and lending situation, I feel that the lender assumes a lot more risk than the borrower.

The first microloan programs were first instituted in Myanmar in the mid-1990s (Soe.) As new laws are passed and as regulations become more lax, there have been an increase in NGOs in the country, making small loans to farmers and small business owners. The exchange rate, interest rate caps, along with high denominations in its currency discourage more NGOs coming in (Soe.) As the program continues to grow, I hope that microloans and microfinance can reach people in areas that still are not developed, or destroyed by the ongoing Civil War. I think that the Myanmar government needs to do more for its citizens, rather than rely on outside humanitarian organizations to provide a basic lifestyle for people who need it the most. This is a difficult problem that I feel would not be solved anytime soon, as lack of financial literacy in its citizens, lack of access to large amounts of credit, and lack of willing lending institutions keeps people stuck in the cycle of poverty.


Schaffner, Julie. Development Economics. N.p.: Wiley, 2014. Print.

Ray, Debraj. Development Economics. N.p.: Princeton UP, 1998. Print.

C. (n.d.). CABI and China boost agricultural development in Myanmar. Retrieved May 09, 2017, from http://www.cabi.org/membership/news/cabi-and-china-boost-agricultural-development-in-myanmar/

Tun, T., Kennedy, A., & Nischan, U. (2015). • Promoting Agricultural Growth in Myanmar: A Review of Policies and an Assessment of Knowledge Gaps (No. 230983). Michigan State University, Department of Agricultural, Food, and Resource Economics.

Htwe, C. M. (2017, March 01). Agricultural sector and SMEs to receive private bank loans. Retrieved May 09, 2017, from http://www.mmtimes.com/index.php/business/25141-agricultural-sector-and-smes-to-receive-private-bank-loans.html

Soe, H. K. (2016, September 06). Can microfinance still make a difference? Retrieved May 09, 2017, from http://frontiermyanmar.net/en/can-microfinance-still-make-a-difference

“Urban Productivity in the Developing World”

Julian Leal

A look at the potential effects of urbanization on developing countries and policy implications.

Glaeser and Xiong, members of Harvard’s Economics Department, in March 2017, released a working paper entitled “Urban Productivity in the Developing World”. Quoting the introduction, the paper seeks to see if “Cities help turn poor countries into rich countries”. The paper looks at several factors to determine this: productivity, density, human capital, and local entrepreneurship.

First the paper looks at the disparity in production between cities. All countries have a production disparity between urban and rural areas. More people are more densely located in cities. Industry and technological improvement is more likely to be in cities. However, the gap between urban and rural areas is more pronounced in developing countries. By understanding why parts of poor countries have become richer, we can improve the whole country. The part examines the correlation between urban density, population relative to area, and productivity in Brazil, China, and India. They use earnings, which in a classical model is equal to the value of a laborer’s production and total firm productivity. The urban-rural wage gap is established in earlier papers (urban areas earning 45%, 122%, and 176% more than rural areas in China, India, and Brazil, respectively). Data from China shows that earnings dispersion is matched with labor productivity dispersion closely (Figure 1). They show differences in labor productivity (by industry) between prefectures (small provincial areas) in China, showing that the productivity gap between the 1st and 2nd most productive is large (60%), and then lessens.


Then they look at the differences across industries in agglomeration (the extent firms locate near firms in the same industry (Silicon Valley, Wall street) and what extent firms locate in densely populated prefectures). 2000-2007 sees a rise in agglomeration in Chinese prefectures. Some industries agglomerate more than others (artificial fibers, electronic music equipment), and more traditional industries (silk-dyeing) have negative agglomeration. Agglomeration is attributed to the ability to share ideas and inputs and access a larger labor and customer pool. Looking at the industry-prefecture’s average labor productivity and the prefecture’s share of total employment in that industry, they conclude that the relationship isn’t linear. Any area with more than 2% of an industry’s employment has good productivity. The relationship between industry employment share and population density of the prefecture correlates positively, though not as much, since manufacturing isn’t urban in most cases (Figure 3).1

Lastly, the correlation between population density and labor productivity is positive, being even slightly higher than that of the U.S. While this could be a misleading effect, most likely these agglomeration economies are legitimate because large cities tend to be more connected to the rest of the world, allowing technology to enter and dramatically boost productivity. Glaeser and Xiang run several correlations and regression between several variables already discussed as well as other variables that would alter them like college degrees and export percentage. The main takeaways from these charts are that industries and firms with higher percentages of employees with college degrees tend to be more agglomerated Information sharing is valuable with knowledge-based fields, so they urbanize to facilitate it. It also provides easier access to the rest of the world. Industries based on exporting tend to be urbanized as they need access to a larger customer base and to special economic zones like ports. While these are the main interpretations, the data shows that the tendency to and returns to urbanization and agglomeration are very industry based.

Next human capital (knowledge and skills) externalities (the benefits of being around smart and skilled people) is discussed. Areas are defined by skill level, so human capital increases will increase earnings. In India, Brazil, and China, these effects are more pronounced than in the U.S. Human capital is important in developing countries because high human capital enables spread of knowledge and skills, where there is a large gap in developing countries. The more urbanized developing countries become, the more pronounced these effects become. Denser populations are in closer proximity to people with higher human capital. Glaeser and Xiang say that developing countries shouldn’t use policy to impose artificial barriers on growth, such as housing limits, to maximize this phenomenon.

Next, they address entrepreneurship’s effects on development. Previous papers looking at entrepreneurship’s affects shows that it makes urban areas resilient to declines and increases employment and establishment size. It doesn’t increase income growth, potentially from the elastic labor supply or the ability of entrepreneurs suppress keep labor costs. Modern ideas conclude that entrepreneurship is a type of human capital, so it behaves as such.

Specifically, in developing countries in Africa, entrepreneurship is low because human capital is low. Economists originally thought that foreign direct investment (FDI) would increase local entrepreneurship potential and allow exporting businesses to flourish. It appears that neither FDI or local entrepreneurship have any effect unless a certain threshold of human capital, not present in many African countries, exists. They lack the knowledge and ability to produce for global markets. What about immigrant entrepreneurs? Several immigrant entrepreneurs are noted: Sergey Brin (Google) and Fernando Duarte (Nando’s), and others from India, Europe, and the Middle East. However, Africa has difficulties attracting entrepreneurs due to its unattractive locales and pushback from local politics and regulations. Making Africa more attractive and easier to access is crucial in policy decisions. Other policy considerations include investing in education to improve human capital and make areas more attractive to entrepreneurs who can better utilize skilled and knowledgeable people. This however doesn’t encourage native entrepreneurship, so potential strategies (little evidence of their effects exists) are entrepreneurial training, providing spaces for clustering entrepreneurs to facilitate learning from each other, and deregulating and removing restrictions that deter entrepreneurs. A combination of these strategies can increase local entrepreneurship and lift businesses to global markets.

Should policy encourage the increase of city size? Benefits and costs exist. Spatially biased policies are dangerous as they favor more politically powerful regions and subsidies may be misplaced. Barriers to urban growth need to be reduced through urban life quality improvement. Cities appear to be beneficial to the economy, so their growth shouldn’t be hindered. Downsides of density in urban areas are disease, congestion, crime, etc. Decreasing these makes cities more attractive to immigrants, as well as encourages productivity. Points to improve urban areas include infrastructure, which can reduce water-borne illnesses, traffic congestion, etc. Infrastructure is expensive and in several instances costs outweigh benefits. Different types of infrastructure providers are discussed, each having strengths and weaknesses. The For-Profit Independent and the Public Integrated are determined to have the most potential, given the presence of strong independent leaders or a non-corrupt government, respectively. Property rights are less clear and aren’t well protected in the developing world. This reduces incentives to invest in property and its improvement. Labor supply decreases because people spend more time protecting property. Property rights make transactions easier when properties are defined and documented, as well as reducing crime.

In summary, this paper promotes the benefits of urbanization of developing countries. Urbanized areas are more productive and attract more educated people and local and immigrant entrepreneurs. Investing in these people and human capital overall is crucial to development. Therefore policy-makers must enact policies that decrease the negative effects of urbanization and not restrict city growth to promote these skilled people.

Original Paper: http://www.nber.org/papers/w23279

Remittances in South Asia and Development Economics

Using a recent report on remittances to motivate a discussion on how remittances play into Developmental Economics

Nafee H. Ahmed


Migrant Workers from South Asia working in Qatar (picture by European Pressphoto Agency)

On April 21 2017, The Times of India published an article which summarized the findings of a recent World Bank Report on remittances. The article referenced a few interesting facts which can motivate a discussion on how remittances relate to development economics. After discussing remittances in depth one can revisit the article to see how well developmental economic theory reflects real world events.

The article highlights that India received more money in remittances than any other country in 2016; Indian workers sent home 62.7 billion American dollars in total. The article also notes that the total amount of money in remittances to India fell by 8.9 percent in 2016 and contextualizes that drop by explaining that the total amount of money in remittances sent to all developing countries fell by 2.4 percent in 2016. The article later reveals that money in remittances sent to South Asia fell by 6.4 percent.

This article claims that the primary cause of migrant workers sending less money home is related to lower oil prices and lower economic growth among countries in the Arabian peninsula; many Indian migrant workers work in these countries lower economic growth in these countries can decrease the amount of money migrants can send home.

The article provides a useful list of the countries which received the most money in remittances. In terms of absolute dollars those countries are India, The Philippines, China, Mexico and Pakistan; however, the countries which take the most money in remittances as a percentage of that country’s GDP are Kyrgyz Republic, Nepal, Liberia, Haiti, and Tonga.

The Importance of Remittances

Remittances are an important topic for two main reasons. Firstly, remittances are major component of the economy in many developing countries. The Times of India article referenced above divulged that remittances account for 6.0 percent of Bangladesh’s GDP, 6.9 percent of Pakistan’s GDP and 2.9 percent of India’s GDP.


Secondly, there is evidence that remittances decrease poverty in developing countries. In 2005, an article in the journal, World Development, by Richard Adams and John Page found a relationship between remittances and poverty. Adams and Page claimed, “both international migration and remittances have a strong, statistically significant impact on reducing poverty in the developing world … After instrumenting for the possible endogeneity of international remittances, a similar 10 percent increase in per capita official international remittances will lead, on average, to a 3.5 percent decline in the share of people living in poverty.” (Adams and Page  1660).


Remittances and Growth


Katushi Imai et al.’s article, “Remittances, Growth and Poverty: New Evidence from Asian Countries,” provides a strong claim that that remittances have a positive relationship with GDP growth. The authors’ model found that, on average, a 10 percent increase in a country’s remittance payments as a share of that country’s GDP increased that country’s rate of growth in GDP per capita. The authors also provide an intuitive explanation for why higher levels of remittances are related to higher economic growth, stating “The existing literature (for example, Barajas et al., 2009) identifies various channels through which remittances enhance growth, including the boosting of capital accumulation, labour force growth, and total factor productivity …” (Imai et al. 530-531).


A link to the article “Remittances, Growth and Poverty: New Evidence from Asian Countries” can be found here: http://www.sciencedirect.com/science/article/pii/S0161893814000209


Applying Remittances to a Growth Model in Development Economics


If one accepts that remittances positively influence GDP growth in developing countries, then one can also look at traditional growth models in Development Economics and apply the value of remittances as an additional variable. Many models in Developmental Economics relate economic growth to other variables. If economic growth has a positive relationship with one variable, then the value of remittances a country receives should also have a positive relationship with that same variable.


Consider two examples with a common model in Development Economics, The Solow Model:
The Solow Model is a common model of economic growth which relates several variables to economic growth. In summary, The Solow model describes economic output as an equation determined by physical capital, labor, the depreciation of physical capital, and the savings rate of a population. More Modern versions of the model add even more variables into this equation including the education level of a workforce and the level of population growth.

An intuitive video series by explaining the Solow Model can be found here: https://www.youtube.com/watch?v=eVAS-t83Tx0&list=PL-uRhZ_p-BM6L_I3IHvE85NHooK2Ln9Rm


One can use the Solow model to find how remittances are related to other economic variables. I created the following two examples trying to fit remittances into the logic of the Solow Model



The Solow model implies that the levels of economic growth in a country decreases with respect to time when holding all other variables constant. Assuming positive relationship between remittances and economic growth then allows the Solow model to imply that the value of remittances a country receives will also decrease with respect to time holding all other variables constant.



The Solow model implies that smaller economies experience higher levels of economic growth than large economies when holding all other variables constant. Assuming the same positive relationship between remittances and growth then allows the Solow model to imply that smaller economies will receive more in remittances than large economies holding all other variables constant.

Back to the Original Article


Looking back to the original Times of India article, we can check if our ideas about remittances derived from growth models match data from the real world. When applying remittances to the Solow model one can predict that over time, countries will receive less money in remittances as a share of that country’s GDP. While the original article does note a decrease in remittances compared to previous years, this is because of factors not related to the countries receiving remittances but rather problems in the countries from which migrant workers send remittances. The original Times of India article also claims that World Bank projections show that South Asian countries will not see significant growth in remittances in the near future. This projection is not necessarily proof that applying remittances to the Solow growth model is correct, especially since the projection was based on factors outside of South Asia, but the World Bank’s projection does not contradict the idea that a developing country might receive less money in remittances over time.


Applying remittances to the Solow model also allows one to predict that the countries which receive the most remittances as a share of the country’s GDP should also be very small economies. The Times of India article confirms this prediction; data from the World Bank database reveals that none of the countries which receive the most money in remittances as a share of the country’s GDP have a GDP per capita higher than 5,000 dollars.


The original Times of India article predicts a decreased level of remittances in South Asia for next year. Given the evidence examined in this blog post, this may have a potential negative impact on economic growth, something which businesses, policy makers, economists, and other observers should note in the coming years.

Works Cited


Academic Articles and Textbooks:

Adams, Jeffrey and John Page. “Do international migration and remittances reduce poverty in developing countries?” World Development, vol. 33, no. 10, Oct. 2005, pp. 1645-1669. Science Direct.


Imai, Katsushi et al. “Remittances Growth and Poverty: New Evidence from Asian Countries.” Journal of Policy Modeling, vol 36, no. 3, June 2014, pp. 524-528. Science Direct.


Mankiw, Gregory. Macroeconomics. 8th ed., Worth Publishers. 2012.


Photographs/ Videos:

Construction workers queue for buses back to their accommodation camp in Doha, Qatar. 19 Nov. 2013. European Pressphoto Agency, Frankfurt. http://www.epa.eu/economy-business-and-finance-photos/sports-events-sports-organisations-soccer-human-rights-heatlh-at-work-construction-property-photos/foreign-laborers-work-in-doha-photos-51109917


“The Solow Model of Economic Growth.” Youtube Playlist, uploaded by Marginal Revolution University. 28 March 2016. https://www.youtube.com/watch?v=eVAS-t83Tx0&list=PL-uRhZ_p-BM6L_I3IHvE85NHooK2Ln9Rm


“India tops global remittances at $62.7 billion in 2016: World Bank.” Times of India, 21 April 2017. http://timesofindia.indiatimes.com/business/india-business/india-tops-global-remittances-at-62-7-billion-in-2016-world-bank/articleshow/58302262.cms


“DataBank World Development Indicators.” The World Bank, 1 May 2017, http://databank.worldbank.org/data/reports.aspx?Code=NY.GDP.MKTP.KD.ZG&id=1ff4a498&report_name=Popular-Indicators&populartype=series&ispopular=y#

Structural Labor Changes in Sub Saharan Africa Could be the Key to Creating Positive Economic Growth

Empirical analysis of recent data suggests that Sub-Saharan Africa is on track to follow the economic growth paths of developed countries, through a structural shift away from the agricultural sector of labor and a diminishing productivity gap. By: Ben Whitacre


The region known as Sub Saharan Africa (SSA) contains some of the poorest countries in the world, known for its economic failure and astounding poverty rates. In recent years, the dynamic of the economy, particularly in the labor force, has generated the first ever recorded positive economic growth rates in this area. The analysis, “The Changing Structure of Africa’s Economies”, performed by Xinshen Diao, Kenneth Harttgen, and Margaret McMillan, seeks to provide evidence that Sub Saharan Africa is beginning to indicate a shift towards the development track that many successful economic countries followed on their way to prosperity. The authors claim that most of the economic progress comes from a structural change of the labor force: a shift from the agricultural sector, to the manufacturing and service sectors. This shift contributed to overall labor productivity growth, and allowed Africa to experience its “strongest growth in four decades” (Diao et al 20).

Basis and Assumptions:

To adequately analyze the economic trends of rural Africa, the authors chose to utilize two data sets: the Groningen Growth and Development Center (GGDC), and the Demographic and Health Surveys (DHS). Between these, there are varying numbers of observed countries, but the eight overlapping countries are specifically targeted for the data analysis. These countries include some of the lowest income African countries such as Ethiopia, Nigeria, and Tanzania. These are compared to some of the highest income African countries such as Botswana, South Africa, and Mauritius, as well as data groups from Latin American, Asian, and highly developed countries (such as the United States). The purpose behind using developed countries’ data was “to study the evolution of the distribution of employment between sectors across levels of income experienced in Africa and how it compares with the patterns seen historically in other regions over the course of development” (Diao et al 12).

For decades, poverty-stricken areas of Africa have largely focused simply on agricultural labor: providing the basic food for the people to survive. The authors believe that a shift in the labor sectors is leading to a decrease in the magnitude of the labor productivity gap, and an increased prosperity level overall. The heart of the paper focuses on the changes in the “level of employment shares” in each labor sector, corresponding to the “levels of income” (Diao et al 6). The logic behind comparing the levels of the structural sections of labor provides the observer the ability to map out trends of shifts based on previously developed nations.

Several assumptions related to the accuracy and availability of the data collected by both the GGDC and the DHS surveys must be made to observe and compare the economic growth in Africa. The authors point out that employment data, informal labor sector knowledge, and measurements of human capital (well-being, education, etc.) are all taken at the level of detail and availability that the surveys provide. Unfortunately, as seen with many studies throughout research, data which comes from poverty stricken countries is not always reliable, accurate/without error. There are instances where the authors of this NBER analysis exclude an entire group of data, justifying their actions as if generalizing groups will “avoid confounding the results” of the data (Diao et al 28). However, the assumptions in the analysis are justified, as the authors took care to check each set of data, inquire the survey agencies regarding errors they found, and base their analysis of trends on data in which two or more benchmark surveys were always provided.


“The Changing Structure of Africa’s Economies” is based on the hypothesis that structural change in the labor sector distribution has a positive effect on economic growth. The author’s stand by their premise by stating that in developed/prosperous countries, there are very few people who are involved in the agricultural labor sector. Reallocating labor in rural areas into sectors such as manufacturing can have a huge increase in labor productivity, thus “allowing aggregate productivity to catch up…[causing] rapid growth rates” (Diao et al 11). In fact, empirical evidence suggests that according to a “GGDC sample, annual labor productivity grew by an (unweighted) average of 2.82 percent, and structural change contributed an (unweighted) average of 1.13 percentage points to overall labor productivity growth. Put differently, from 2000 to 2010, structural change accounted for 40 percent of Africa’s annual labor productivity growth” (Diao et al 24).As observed in Table 1, for the majority of African countries the labor sector with the lowest productivity is agriculture: with a maximum value of 4.37.

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Table 1: Diao, X., Harttgen, K., & McMillan, M. (2017, January). The Changing Structure of Africa’s Economies

By improving the labor productivity growth, the overall growth rate of the economy increases, poverty rates decrease, and human capital increases by creating skilled workers. The manufacturing sector in Africa may never compare to the manufacturing industry in a previously developed country, but it has been shown that African areas who devote their resources into building human capital to provide skilled manufacturing works generate higher levels of income to raise the poverty headcount ratio at drastic rates. Although some of these labor sectors are specialized and do not have the capacity to bear all structural change, there is a positive observable correlation due to structural transformation ASSUMING the transfer of labor ends up in a more profitable sector. Transfer of labor to a less profitable sector can lead to recession of economic growth. Because of this risk, it is often profitable to look within sectors to make infrastructure changes. Related articles, such as a USDA Economic Research Service report written by Keith Fuglie and Nicholas Rada, indicates that although a transfer in internal-sector productivity may be useful, doubling agricultural research can also boost Total Factor Productivity (which compares total outputs to total inputs in a country) growth rates by over 4%. According to the GGDC data, the initial benchmark revealed low-income countries exhibited an approximate 70% of their labor force was dedicated to agriculture, a number with declined by 9.3% by the time the most recent data was observed (Diao et al 24). This led to an increase of over one and a half percentage points in labor productivity and in some cases, positive country economic growth rates.  Studies in the GGDC data, and the DHS data (categorized by gender, education, age, etc.) showed similar improving results with the decrease in agricultural labor – with the greatest difference being observed with females in rural areas. Figure 1 demonstrates the decline in the GDP level per capita of Agriculture, while contrasting with the increase of GDP wealth per capita in other labor sectors.

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Figure 1: Employment shares by labor sector, increasing/decreasing with income: Diao, X., Harttgen, K., & McMillan, M. (2017, January). The Changing Structure of Africa’s Economies


Daio, Harttgen, and McMillan chose to analyze two data sets to expand research on Africa’s upcoming economy that had previously never been approached. What they found was that distinct patterns were found in the structural trends that can be compared and adjusted by observing the development paths of previously poverty stricken and underdeveloped nations. In fact, at “lower levels of income, countries that pull themselves out of poverty also exhibit positive structural change” as a critical part of their economic development. Now, not every sector of expansion that prospered in a different country (ex. Latin America) will work in rural Africa, but similar growth concepts, such as the “importance of investing in human capital and infrastructure…can raise productivity levels” and improve a country’s overall state of well-being (Diao et al 32). The authors summarize their findings with 5 stylized facts listed below, which begin to outline growth patterns based on structural shift. The largest implication of this paper however, is to open the door for more empirical analysis and research in sub Saharan Africa, as the authors state that until this point, “economic data to undertake such analysis has been largely unreliable or nonexistent for most African countries” (Diao et al 12).

Stylized Facts:

  • “First, when the patterns of employment in Africa are compared to the patterns observed in other regions across levels of development, the pattern among our sample follows that seen in other regions for agriculture and services—that is, the agricultural employment share is decreasing in income, while the services employment share is increasing in income.”
  • “Second, when the levels of employment shares are compared to the levels observed in other countries, the levels of employment shares in agriculture and services approximate the levels observed in other countries at similar levels of income.”
  • “Third, all of this holds for industry and manufacturing in the eight low-income African countries.”
  • “Fourth, in Botswana, Mauritius, and South Africa, the patterns in industry are similar but the levels differ, and in the case of manufacturing, the relationship between income and employment shares follows more of an upward sloping line than an inverted U-shape.”
  • “Fifth, Africa is still, by far, one of the poorest regions of the world.”
  • “Finally, structural change continues to remain a potent source of labor productivity growth in much of SSA.”

Stylized Facts Courtesy of Daio, Harttgen, and McMillan, “The Changing Structure of Africa’s Economies”.

Works Cited

Diao, X., Harttgen, K., & McMillan, M. (2017, January). The Changing Structure of Africa’s Economies (Working paper No. 23021). Retrieved April 19, 2017, from National Bureau of Economic Research website: http://www.nber.org.proxy-um.researchport.umd.edu/papers/w22872.pdf

JEL No. O11,O4,O55

Fuglie, K., & Rada, N. (2013, May 6). Research Raises Agricultural Productivity in Sub-Saharan Africa. Retrieved April 24, 2017, from https://www.ers.usda.gov/amber-waves/2013/may/research-raises-agricultural-productivity-in-sub-saharan-africa/

To be ,or not to be? The current challenge of Chinese Micro-credit companies

A general introduction to China current micro-credit market, and an in-depth analysis of micro-credit market competition.
By: Ming Zhou

News Review:

The Chinese economy has experienced a significant economic growth over the last few decades, and base on the empirical study from Burgess and Panda, there is a strong correlation between economic growth and financial development. The concepts of Micro-Finance was introduced by Mohammad Yunus in mid-1970s, Microfinance is a program which offers credits, savings and other financial services to poor household or individual who cannot afford services from the commercial bank. (Julie Schaffner)

According to Xinhua news, the article “Outstanding loans of Chinese micro-credit firms hit 929 bln yuan in September” states China’s microfinance market has grown exponentially and the total amount of outstanding loans reached up to 137 billion U.S. dollar on Sep, 2016, with 8,741 companies which are related to Microfinance market. Much small-medium businesses or individual households have been benefiting from access to a small loan. The Chinese government encourages the ongoing investment activity to these little businesses, which can be explained by the concept of the Solow model. As more and more entrepreneurs choose to open business, this is more likely to generate more ideas; a good idea could often transform to new technology. Technology is substantial to economy growth; one good illustration of this theory is by comparing South Korea and North Korea. South Korea is more technological advanced than North Korea and hence it has a much stronger economy.

Competition in the micro-finance market, a general landscape:

Although many small business benefits from the blooming micro-credit market, the micro-finance market is still facing some challenges.  Lenders face strong adverse selection due to an unsound information system in China. Micro-finance companies also facing strong competition from commercial banks. Unlike the situation explained by Julie, Commercial Banks have a large market sector in China micro-credit market; many commercial banks have micro-credit sector that offer loan to small and medium enterprises. Aside from commercial banks, Micro-credit companies also face competition from rural finance and online finance such as P2P lending. Rural finance offer loan for agricultural purpose. On other hand, with easier access to the Internet, online finance has raised some world-known corporations such as Alibaba which offers similar finance service to small enterprises, who trade goods through the Alibaba’s platform. Microcredit companies in China targets finance for small enterprise rather than individuals. (Jeffrey Riecke) And this is consistent with the news article, as Jiangsu Province has the most amount of micro-credit companies, the region is well known for business activity base on its geography advance.

One interesting insight I got from a journal on the China Story, author Luke Deer illustrates the boom of China micro-finance offers many access to small enterprise. However, the cost of borrowing is much higher than similar program in developed economy. According to the survey, the rate of borrowing offered by the Rural Cooperative Banks was 13.8% for a annual loan, which is three times higher than China’s official lending rate at that period. The article points out although the cost of borrowing was high, households still prefer to borrow from the rural program, rather than informal borrowing from family and friends, is the program offer service which comes with low transaction cost and shorter period of time, and the process is transparent which reduce asymmetric information. (Luke Deer) This finding is consistent with Julie’s theory, when transfer costs are low and markets are well integrated, entrepreneurs can produce output in a cheaper price as input is cheaper.

The Challenge:

The boom of China credit market not only benefits the small enterprises, but it also provides opportunity for lenders as well. Most of the owners of micro-credit companies do not have proper knowledge on operating properly compared to developed countries. For instance, the owner may only consider lending money out as a “capital game,” which is a method to increase their personal wealth by offering a high-interest loan. The only focus on return does not benefit the business in the long run, as lack of standardized management and ambition to expand the business will eventually terminate many micro-credit companies in the future.

Unlike the commercial banks, micro-credit companies have limited amount of fund for loans. Without proper risk management and sufficient information access, micro-credit lenders face high adverse selection. Likewise, since commercial bank has also started to enter the micro-credit market, micro-credit companies’ faces increased risks as lack of competition, regarding lending rate and ability to lend. Moreover, as Jeffrey mentioned in his article, these companies have low access to credit reporting information from the central bank of China. I think although the government does encourage the activity of micro-finance, local government does not provide sufficient help to these lenders. Likewise, the government does not give a specific guideline or regulation on the micro-finance market. Many lenders can enter the market easily, facing direct competition from the commercial bank, one thing worth mentioning is four out of five commercial banks in China are owned by State. China economy is complicated as it is half capitalism and half socialism. Although the government tries not to intervene in the market, the existence of State-owned enterprise creates a disadvantage to other, as state-owned enterprises have more connection and can easily gain information or help from the government.

In the long run, I think the micro-credit market will well divide into smaller segments as market specialization increase companies’ ability to survive. A significant amount of small micro-credit companies will be eliminated; the remaining will transform to rural finance as they do not have the ability to compete with the commercial bank in the urban area. On the other hand, smaller companies might merge or collaborate with each other to compete with the commercial bank or be acquired by the commercial bank as a retailer in the rural area.

Works Cited

Outstanding loans of Chinese micro-credit firms hit 929 bln yuan in September. (2016, October 25). Retrieved April 24, 2017, from http://news.xinhuanet.com/english/2016-10/25/c_135780038.htm

Schaffner, J. (n.d.). Development Economics: THEORY, EMPIRICAL RESEARCH, AND POLICY ANALYSIS (Chapter. 21). Tufts University.

Deer, L. (2014, September 17). A Springtime for Microfinance in China? Retrieved April 24, 2017, from https://www.thechinastory.org/2014/09/a-springtime-for-microfinance-in-china/

Riecke, J. (2015, March 12). China’s Microfinance Landscape: Nonprofits, Microcredit Companies, Rural Financers, and Alibaba. Retrieved April 24, 2017, from https://cfi-blog.org/2014/09/23/chinas-microfinance-landscape-nonprofits-microcredit-companies-rural-financers-and-alibaba/