Will Technology Solve Kenya’s Economy?

Examining the economic impact of increased investment in technology in Kenya.



Technology is believed to be the key to the future by unlocking the answers to our problems of today. The level of technology a country has greatly impacts the country’s economy through both the demand and supply side. Recently it was reported by Elizabeth Merab at The Daily Nation that Melinda Gates has launched a new program called Pathways for Prosperity: A New Commission on Technology and Inclusive Development in Kenya. The point of the program will be to figure out ways to help advance technology in developing countries in a way that enriches the economy. Another key part of the program is making sure that all the efforts are equally distributed between the rich and the poor to help close the inequality gap. In this blog I will discuss the current problems facing Kenya’s poverty rate before moving into how technology impacts the economic models of output and income inequality.

Poverty in Kenya

Poverty levels in Kenya are still considerably high compared to other countries today. Currently over thirty six percent of the population in Kenya is living below the poverty line(World Bank). What this means for those living under the poverty line is that they are unable to meet the basic income needed to consume at the standard of living to survive. The issue that Kenya is facing the World Bank states, is that they are unable to transfer their steady growth domestic product(GDP) level to consumption making their reduction to the poverty rate miniscule each year.  This though isn’t their only problem when solving their poverty problem, because Kenya is also facing a massive inequality gap. Meaning that their richest twenty percent of the population makes eleven times more than their poorest twenty percent of the population(Business Daily). Both high poverty rates and high inequality rates are currently hurting Kenya’s economy.

Neoclassical Model and Technology

Having a better grasp on the current problems, we can begin to look at how technology would solve these problems. The World Bank stated that Kenya needed “higher and more inclusive growth rates”, which Melinda Gates believes her program will provide by having technology stimulate productivity. This stimulation of productivity would lead to an increase in GDP and eventually a decrease in poverty due to higher wages and higher levels of employment. To fully understand the impact of technology on Kenya’s economy it is important to first examine the Solow’s Neoclassical Model of Growth. This model shows the country’s economic growth by looking at its labor, capital, and productivity. Looking at the original model with technological constraint shows what Kenya’s steady state of economic growth would look like. The steady state is what all economies are striving for where there is no economic growth because they are at a perfect level where everything is equal.  This is would be marked by k on the graph.



The impact of technology on the economy is best explained by looking at how it would impact it at its steady state. The increase in technology would shift the curve upwards due to an increase in productivity and labor, causing an increase in both the capital and output levels as shown in the diagram below.


What this means is that economy would expand and the growth rate would increase. Increase in technology is believed to then have a positive impact on the reduction of poverty rate of a country. This kind of increase in productivity shown in the graph above will have a positive impact on everyone in the market. This kind of conclusion was also stated in a recent article by the Brookings Institute claiming that “technology can exponentially facilitate the achievement of development goals through rapid scale” (Chan).

Taking Down Inequality

The problem left over from the enhancement of technology would be the inequality gap. The reason this would still be an issue is that Melinda Gates wants to have the technology equally distributed between the rich and the poor(Merab). What this would do is cause everyone to increase their income as shown above at the same rate. This would shift more people over the poverty line, but would also move more people already above the poverty line higher. The gap wouldn’t decrease but just shift upwards as a fallout then from the technology.  The inequality gap doesn’t disappear with an increase in GDP and a decrease in poverty. Inequality gap has to be directly addressed because its deep rooted in the economic history of the country.


In conclusion technology can greatly impact the poverty levels of a country by increasing its productivity and GDP. An issue that can arise is that if technology is equally spread out among the people it won’t help in reducing the inequality in the country. The article states that the commission plans to do research on the best ways to implicate the new technology and hopefully that will help to solve this dilemma. When doing their research the commission should take into account the benefits of starting the technology with the poor before spreading it to the wealthy. Overall though this new program should benefit Kenya greatly in moving them towards a more prosperous economy.



Source Article :

Merab, Elizabeth” How Melinda Gates PLans to Promote Growth in Africa”. Daily Nation. January 28, 2018. Web. https://www.nation.co.ke/news/How-Melinda-Gates-plans-to-boost-growth-in-Africa/1056-4282486-nhhn23z/index.html


Wide wealth gap leads to calls for pro-poor policies”. Business Daily. August 25, 2014. Web. https://www.businessdailyafrica.com/news/Wide-wealth-gap-leads-to-calls-for-pro-poor-policies/539546-2429628-991358/index.html.


Chan, Rosana. “ Foresight Africa viewpoint: rethinking African growth and service delivery: technology as a catalyst.” Brooking Institute. January 12, 2018.Web. .https://www.brookings.edu/blog/africa-in-focus/2018/01/12/foresight-africa-viewpoint-rethinking-african-growth-and-service-delivery-technology-as-a-catalyst/

“Poverty Incidence in Kenya Declined Significantly, but Unlikely to be Eradicated by 2030”. World Bank. April 10, 2018. Web. http://www.worldbank.org/en/country/kenya/publication/kenya-economic-update-poverty-incidence-in-kenya-declined-significantly-but-unlikely-to-be-eradicated-by-2030


A Discussion on the Economy of South Africa: Past, Present, and Future

By: Brian Williams


Good economic news has recently come out of South Africa, as the country experienced 3.1% GDP growth in the fourth quarter of 2017, and is now projected by the World Bank to exceed an earlier projection and have GDP growth reach 1.4% in 2018. While this is certainly something to take pride in, South Africa has some lofty goals for their future economic growth, as the government’s ambition is to achieve a 5% growth rate in the coming years. This post will analyze the historical growth of South Africa to gain a better understanding of future growth prospects for the Rainbow Nation.

Government Policy Analysis

In order to sustain and even improve growth, Paul Noumba Um, South Africa’s World Bank Director, acknowledged that GDP growth in his country is being challenged by unemployment, inequality, and poverty.[1] The GINI Coefficient, a measure of the inequality of a country with values between 0 and 100%, is very high in South Africa relative to other countries at 63. This means that a small percentage of the population owns a large proportion of the wealth.[2]

GINI index
The GINI Index of South Africa and important countries

     The South African Department of Trade and Industry highlights that companies will have a large pool of both semiskilled and unskilled workers to potentially employ as a major draw for investment, which would reduce the high inequality prevalent in the country, as well as help grow the economy with more people working.[3] To reduce poverty and close the inequality gap, Julie Schaffner’s textbook on Development Economics describes government policies that take into account the financial constraints the poor are faced with, such as bringing markets into remote areas whose inhabitants are commonly poor due to their large proximity away from financial centers, along with policies that “explicitly create new assets owned or used by the poor,” as the most effective. These policies perform multiple tasks, as they promote a reduction in inequality along with promoting growth in the economy with equal success to policies targeting those with average income.[4]

 BRICS Analysis

To get a better picture of South Africa’s future, it’s past economic progress can be a useful guide. BRICS is an acronym used to group the countries of Brazil, Russia, India, China, and South Africa together. First established by Goldman Sachs economist Jim O’Neil in 2001 to identify strong, growing economies, BRICS has advanced into “a new and promising political-diplomatic entity, far beyond the original concept tailored for the financial markets,” with Summits between member countries held annually and group decisions made often.[5] In his paper Divergence, Big Time, Lant Pritchett studied the average growth rates of 17 currently high-income countries from three different time periods. Divergence in this case is defined as the state when the GDP per capita of wealthy countries increases quicker than the GDP per capita of other countries, creating a greater divide between the two groups.[6] The table below presents a similar study to Pritchett’s, conducted with data for the BRICS countries over three different time periods.

GDP Growth Rate.png
Growth Rates of BRICS countries over 3 different time periods

One observation from this analysis is how South Africa has fallen from having the highest GDP per capita to having the fourth highest of the BRICS countries. Couple that with their consistently low average growth rates relative to the other countries (1.80, -0.467, and 1.586), and it becomes a signal that South Africa is diverging away from countries like Brazil, China, and Russia in terms of economic growth per capita.

OECD Analysis

The economies of the BRICS countries are often thought of as less developed relative to the advanced economies of the world, which are typically considered to be the OECD countries. Pritchett defines the OECD countries as European countries, their offshoots, and Japan. In his work, Pritchett estimated “that from 1870 to 1990, the ratio of per capita incomes between the richest and the poorest countries increased by roughly a factor of five,” which is a signal that divergence had occurred between the “developed” OECD countries and the other “less developed” countries.[7] By comparing the adjusted income per capita of South Africa and the OECD member countries, as shown in graph below, it becomes apparent that the divergence Pritchett discussed has occurred here as well.

Income per capita divergence.png
Income per Capita Divergence between OECD countries and South Africa

Numerically, the World Bank estimates that in 1971, the adjusted income per capita in South Africa was 728.245, while for OECD member countries it was 2,547,569. Had convergence occurred between these two countries, it would be expected that this gap of approximately 350% would have been reduced by today as South Africa’s economy would have grown faster than the OECD member’s economies, but this is not what happened. In fact, the current adjusted income per capita of South Africa is estimated to be 4,258.973, while this statistic for OECD member countries is now approximately 30,785,193, over 700% greater than South Africa’s. This exceeds Pritchett’s estimation and shows a high degree of divergence between South Africa and the developed OECD countries.[8]

Future Growth Potential

Even with the positive news of growth for the South African economy, the government still believes that higher growth rates can be achieved. Taking a step back, it may be ideal for the South African Government to decide if this goal is actually feasible and sustainable. One calculation that can help determine a countries future growth is based off of the observations from a graph included in the 1997 paper On the Evolution of the World Income Distribution penned by Charles Jones. Jones compared a countries 1960 GDP per worker to that of the United States and found that for most countries, those that had a GDP per worker greater than 15% of the United State’s converged, or grew towards the same value, whereas those with a GDP per worker less than that figure saw divergence.[9] For our experiment, we will compare South Africa’s 2016 GDP per worker to that of the United States use that to determine if convergence or divergence will occur in the future. No assumptions were made about the countries in Jones paper, as he simply observed a result from the raw data. The table below describes this relationship between South Africa and the Untied States, the reference country.

Jones analysis.png
Analyzing South Africa’s potential for future growth

Dividing 13614.28556 by 114512.8955 yields the approximation that South Africa’s ratio is 11.889% that of the United States. This is below the 15% threshold Jones observed for divergence, so if his findings hold than South Africa should be expected to further diverge away from the United States. As a result, with this evaluation, South Africa will not achieve their target goal of 5% growth, as they will be expected to grow slower than the United States, a country that averages around 2% growth annually.


[1] Winning, Alexander. “World Bank Raises South Africa 2018 Growth Forecast.”

[2] GINI Index-South Africa. Raw data. The World Bank.

[3] “Why Invest in South Africa.” Trade, Exports & Investment.

[4] Schaffner, Julie. Development Economics: Theory, Empirical Research, and Policy Analysis.

[5] Rachid, Biatriz. “Information about BRICS.”

[6] Pritchett, Lant. “Divergence, Big Time.”

[7] Pritchett, Lant. “Divergence, Big Time.”

[8] Income per Capita-South Africa and OECD countries. Raw data. The World Bank.

[9] Jones, Chad. “On the Evolution of the World Income Distribution.”

Source Articles:



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#