Showing posts with label macro. Show all posts
Showing posts with label macro. Show all posts

Sunday, August 12, 2012

Recipes for economic growth, ingredients and all



Everyone knows that Africa’s economies have recently taken off. Rising Africa has become a cliché phrase in economic articles. But what does the rise exactly look like and what contributes to that? 

With the help of World Bank income data, it is easy to see that the Sub-Saharan Africa has indeed experienced over two-fold increase in incomes during the last decade. Below, I have marked with a blue line the Gross National Income (GNI) levels per capita during the first decade of 2000. We see that the income levels have increased significantly. In order to put income levels of last decade into context, I have added a red line marking the average GNI levels during the three previous decades, from 1962 to 1999, and a green line marking the previous peak income in 1979. See below: we can see that Sub-Saharan Africa has never seen so high GNI levels per capita before.

While it is true that income levels alone are not sufficient to illustrate the economic situation of the entire continent consisting of 54 countries, we can nevertheless conclude few things from that chart below: first, despite the complaints of Africanists and African scholars against The Economist’s simplistic labelling, the simple comparison of Sub-Saharan income levels indeed seems to justify tagging Africa “hopeless” in 2000, “rising” in 2011.


Now, it is much more difficult to say what exactly contributes to the growth. In an attempt to narrow my focus in Africa further down, I have chosen only one country – Rwanda – for my economic analysis, for which I have used 1984-2009 data from World Bank. 

But data alone are not enough. One also needs some models regarding how to use that data. If you wish, economic growth models can be considered like recipes for economic growth, each with particular ingredients. Regression analysis, which can be considered as cooking (again, to bring a lousy parallel) allows me to make a causal claim about how these ingredients in those recipes condition the outcome. Or – what recipe with what ingredients best cooks the economic growth?

All three models, which I picked: namely the Rostow’ stages of growth, the Harrod-Domar model, and neo-classical model – attempt to give the best formula for the economic development. As you see below, they have slightly different ingredients, and different number of ingredients, as well.

Which one of them offers the best recipe for growth? 


Rostow’ stages of growth

The Harrod-Domar model

Neo-Classical Model



1.    Savings,
2.    Investment,
3.    Population growth;
1.  Level of savings,
2.  Productivity of capital (or national capital–output ratio, in inverse relationship);
1.  Capital accumulation (in other sources savings rate),
2.  Population growth (or labour growth),
3.  Productivity, and
4.  Technological progress.

One problem was to find correct, matching data for all those ingredients. Although World Bank offers a wide range of data – starting from the classic GDP to the number of mobile cellular subscriptions and to the number of newborns protected against tetanus to the rate of condom use among youth, I nevertheless had difficulty finding exactly matching (and consistent) data. Like trying to cook exotic cuisine at home, I had to replace some ingredients.

For example, while preparing an old-fashioned Rostow’ stages of growth, which required savings, investment and population growth, instead I used ‘gross domestic savings’, and ‘foreign direct investment’, both measured in current US dollars. I also used size of the total population for the third ingredient: population growth.

As a result of running scatterplots and regressions analyses to explain how do these three ingredients contribute to the GDP growth, I found that savings, population and investment explain impressingly large share of the growth outcome: 91.8 per cent!

This means that countries seeking to boost their GDP should try to find ways to increase their level of savings and investment in addition letting their population grow.


I found this outcome quite surprising as the Rostow’s model is considered to be out-dated. Old-fashioned, as I said. Moreover, it must be mentioned that the single ingredients in this model did not quite correlate perfectly to the GDP. See, for example, how the graph above illustrates correlation of population size to GDP: it is not linear. There are periods, where GDP goes down while the population grows. This tells us that African 'demographic dividend' alone is not sufficient to guarantee economic growth.

Second model on my list, the Harrod–Domar model has only two ingredients. Will it beat the Rostow's model in explaining GDP growth?  Harrod-Domar model tries to explain economy's growth rate in terms of the level of savings and productivity of capital. Therefore, it only has two components. Again, I found it is hard to measure productivity. That is why I replaced ‘productivity of capital’ with ‘national capital / output ratio’, which was available in World Bank dataset. The peculiar thing about measuring capital / output ration is that - the its smaller value, the higher the productivity is: its value correlates negatively to the growth. 

For example, compare the 100-dollar-output produced by 1000 people (which is 10), with the same output worth of 100 dollars produced by fewer, 900 people. The outcome is smaller, 9. That can be shown on the graph below – the higher the productivity (the smaller the value), the bigger the GDP.



Compared to the previous recipe, the Harrod-Domar model explains much smaller share of GDP, as I found after running regressions with the two ingredients. My smart computer program SPSS calculated that only 73 per cent of economic growth is explained by those two ingredients. This tells us that one needs more ingredients (and likely another model) to cook a good economic growth.

And the last one...
Now, lets look at the last, neo-classical model as it is called. For this "recipe" there are different ingredients listed in different sources. It consists of productivity, population growth (or labour growth), capital accumulation (in other sources savings rate), and technological progress.  For consistency, I was using total labour force / GDP ratio as a proxy for productivity as I did with the previous model, and the same indicator for population growth as in Rostow’s model. But instead of required capital accumulation, I found a ‘gross capital formation’ indicator in the World Bank databank.

But how to measure the required ‘technological progress’? There is no exact indicator provided in the Worldbank data for Rwanda. I had to decide: which one is better replacement: the high-tech export, measured in current US dollars, or number of scientific and technical journal articles published annually in Rwanda?

In order to decide, I tested them in correlation to the GDP… How do they relate to eachother?



Since the slightly better match to GDP growth was offered by the number of scientific articles published in Rwanda (see below),  I choose this indicator for the fourth required ingredient of technological progress. (It is quite funny, if you think that the number of journal articles can have anything to do with economic growth.) My computer program did not laugh though – it liked all the ingredients in this recipe, and as a result of regressions, I can claim that together they explain an astonishing 98 per cent of economic growth (while the result is statistically significant)!

This means that based on Rwandan data from three decades, it can be suggested that the leaders who look for recipes for economic growth, could consider the guidance offered by neoclassical model. 

Therefore, capital accumulation (or rate of savings), population (or labour force) growth, productivity, and technological progress will most likely lead to the best outcome in economic growth.

Comparing the models and the outcomes, I realised that the recipe with more ingredients will explain the outcome in GDP growth the best. Neo-classical model has four variables and it provided the highest percentage of GDP growth explained. Therefore, we can conlcude that there is no single magic bullet for prosperity – instead, improvement in a wide variety of factors is necessary.

But is it possible to claim which of those ingredients or independent variables is most powerful?  Yes, based on regression analysis, the rise in productivity seems to be contributing to the GDP growth the best – every unit reduced in labour force /GDP ratio seems to be contributing the biggest rise in GDP growth of all other independent variables. Therefore, it seems clearly: the higher the productivity, the higher the GDP growth. 

-xxx- 

Thursday, March 15, 2012

To liberalize or not?

To liberalize or not, this is the central question in debates about the economies of developing countries. As the three Baltic countries and Estonia in particular have been considered[1],[2] as most successful former Soviet Union country out of 15 member states[3], in my paper I will explore which events had led to macroeconomic success. I will also evaluate the downsides of current macroeconomic situation, which carry a significant social cost. To a degree, my paper would be immersed in the debate whether (neo)liberal policies contribute to economic growth of developing countries.

What causes macroeconomic growth?
Estonia, a small country on the Baltic Sea shore[4] owes its macroeconomic growth to many eco-political decisions. But other, perhaps equally contributing factors are peaceful separation from Soviet Union (SU), geographical proximity to Nordic countries[5] and relative strength of institutions, together with the readiness to reform, which was further catalyzed by a desire to join European Union.

As Thorvaldur & Eduard (2009) assert, a conflict-free breakup from the SU gave Estonia an advantage over some other former SU (fSU) member states like Moldova, which enjoyed a similar economic level during the Soviet period. Lack of conflict allowed Estonia to avoid low-income trap, which both Moldova and Georgia fell into. As a result, Estonia did not suffer from high levels of corruption[6] and was able to reform its institutions. Compared to other fSU countries, its institutions were more effective in fighting shadow economy. The relatively small black market share contributed to an enlarged tax base and consequently to higher income, as Gylfason & Hochreiter suggest (Gylfason & Hochreiter, 2009).
Estonia, together with other Baltic countries benefitted from their proximity to Nordic countries, as Gylfason & Hochreiter claim: “when foreign markets collapsed in the early 1990s, Estonia was able to win new markets for its exports remarkably quickly in Western Europe” (ibid). Attractive opportunity to become an EU member country acted as a catalyzing tool for speeding up institution building and as a result, the recovery after the collapse of the Soviet Union economy was relatively fast. This was interrupted only by a “short-lived slowdown in 1999-2000 due to the Russian crisis” (Deroose, Flores, Giudice, & Turrini, 2010).

Another contributing factor to macroeconomic growth stemmed from the exclusion of the former Soviet political elite from power, as they were not unified as a political party. As a result, due to the elimination of the former elite from decision making, Adam, Kristan, & Tomšič note that “ideological standing of new Estonian political elite of early 1990ies played an important role in determining the type of capitalism pursued”. Unlike most of Eastern European countries, where former communists held on to the power, Estonia established (neo)liberal macroeconomic policies (Adam, Kristan, & Tomšič, 2009) – diametrically opposite from the Soviet centrally planned economy. Estonia established a flat income tax[7], opened up its economy, abolished tariffs for imports and kept a balanced budget or a very small deficit. The so-called Chang’s ladder – protectionist measures for promoting infant industry growth (Chang, 2003) was never used. These macroeconomic measures allowed massive foreign direct investment to flow into the country.

How to measure economic development?
There are many indices to measuring the levels of living standard. Income levels, GDP and the Human Development Index (HDI) are most widely used. Estonian average income, which started declining in 1990 (an average Estonian then earned 10,300 dollars annually in PPP dollars), by 1994 had fallen to the 1970 level – 7734 dollars! Poverty increased and the life expectancy shortened drastically during first couple years of re-independence.
The negative income trend was eventually reversed in 1994 and income consequently doubled during the next 10 years, while Estonia pursued (neo)liberal policies. As authors from European Commission, Directorate-General for Economic and Financial Affairs claim, the reform process was highly successful in reorienting the Baltic economies towards a market system, and thus helping these countries become eligible for EU accession in 2004 (Deroose, Flores, Giudice, & Turrini, 2010).

Estonia enjoyed unusually high growth in the mid-2000s – even by the standards of emerging economies (ibid.) – during which period the structure of the economy was changed. Previously a mainly agricultural country with Soviet-style heavy industry was turned into a subcontracting nation for services and IT[8], with a strong tourism sector. It was during the boom of early 2000s when Estonia was called to be one of the Baltic Tigers, distinguishing itself from other Eastern European and fSU countries[9].

In 2007, a year before the global financial meltdown, Estonians earned on average 19.705 PPP dollars[10] which is significant enhancement when compared to the early years of re-independence. By 2010, the income levels have reached parity with formerly communist Central European countries like Hungary and Poland, which used to be considerably better off. Considering the speed of catch-up in income levels, this fast progress indeed shows that liberal economic policies can, in some cases, contribute to the economic growth.

Earlier I measured the rise in living standards loosely through income rise in PPP dollars[11]. Now, I would like to amend the picture by adding HDI and other measurements to picture. Although considered to be an alternative to the money-centric measurement of well-being[12], HDI nevertheless includes economic measures in its formula. HDI does not seem to be satisfactory in portraying the price the people had paid for the economic growth. During the boom years, it was clear that the generated wealth was not distributed equally within the country, giving social scientists a reason to identify “Two Estonias” – one poor, the other better off.  For example, the most recent analysis composed by the Ombudsman of Estonia (Chancellor of Justice, 2011) shows that almost every fifth child in Estonia in 2010 lived in poverty due to inequality.
The ratio of total income[13] received by the top quintile to that received by the lowest quintile of the population is 5.0. Although this ratio does not differ from the European Union average, which is similarly 5.0 (Statistics of Estonia), the inequality has indeed risen since the 1989. Largely, in accordance with Kuznets’s reversed U, according to which economic growth first raises the inequality and later it levels out (Cypher & Dietz, 2004), the Estonian inequality graph seems similar to an inversed W.
Gapminder visualisation tool for the health and wealth of countries makes the picture of economic development even more complicated. For example, in highly unequal and somewhat poorer Mexico people enjoy better health than Estonians. Does this mean that economic success has negatively influenced people’s health, regardless of increased life expectancy? Similarly, the OECD Better Life index, which visualises the quality of life as flowers, shows the lopsidedness of Estonian flower petals, where Life Satisfaction is significantly shorter than other petals such as  Education[14]

Would neoliberal policies also alleviate economic downturns?
Similarly to my earlier speculation[15] about a likely correlation between (neo)liberal economic policies at the presence of some other favourable conditions and increased income levels, I am curious about what helps countries in deep recession?  In the case of open economy, it has been argued that the government’s ability to control the destructive globalized economy is limited (Held & McGrew, 1993). And what to think of Nobel prize winning economist Joseph Stiglitz’s recent comments the media: that the austerity measures Europe is planning to introduce would be suicidal?

The truth is that an open economy has not only raised income and the quality of life, but it has consequently opened Estonia to severe global crises. An open economy has brought a very short boom and bust cycle and severe economic meltdowns, during which the GDP growth was negative (-14 per cent in 2009). The Estonian government nevertheless introduced severe austerity measures to control the situation in 2008. These processes resulted in lower salaries (approximately by nine percent) while personal debt of many people had increased[16]. Despite that shocking downturn, Estonia’s economic decline was not so sharp compared to the massive economic failure of neighbouring Latvia, which needed assistance from IMF[17]. Regardless of this comparison, Estonian unemployment rate in 2010 was nevertheless a staggering 16.8 per cent.

Two years after introducing austerity measures, The Economist magazine reported in July 2011: “Plunging unemployment, rocketing growth, soaring exports and a budget surplus: that is the story of Estonia as it bounces back from a precipitous economic collapse.” The point The Economist wanted to convey was that austerity measures and strictly balanced budget guarantee a fast recovery after a severe economic meltdown, as the competitiveness of the country increases and it is therefore again able to attract investments. The Estonia.eu website claims that in 2010, the annual GDP grew by 3.1 per cent compared to the previous year. According to the 2011 forecast of the Ministry of Finance, the economy will grow in 2011 and in 2012 by 4 per cent[18], which is likely the highest growth rate in Europe.

Conclusion
Even if in the strictly economic sense the liberal policies and shock therapies have increased the incomes and improved the health of Estonians, people are increasingly tired of the sudden boom and bust cycle. Strikes organised by Estonian teachers and nurses prove that. I agree with the OECD recommendation on its website: “… to reduce the vulnerability of the poor and help them adjust to make the most of new opportunities that are created … open markets require parallel investments in human capital (education, health and nutrition) and physical infrastructure, access to credit and technical assistance, as well as social safety nets and policies to promote stability” (OECD). Although Estonians are relatively well educated, the health and nutrition (especially those of children) and social safety nets would need additional investment.


Bibliography


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Brixiova, Z., Vartia, L., & Wörgötter, A. (2010). Capital flows and the boom–bust cycle: The case of Estonia. Economic Systems , 34 (1), 55-72.
Cato Institute. (2006, May 18). Cato Institute. Retrieved February 14, 2012, from http://www.cato-at-liberty.org/mart-laar-friedman-prize-winner/
Chancellor of Justice. (2011, February 13). Vaesus ja sellega seotud probleemid lastega peredes. Retrieved February 15, 2011, from http://oiguskantsler.ee/sites/default/files/ulevaade_vaesus_ja_sellega_seotud_probleemid_lastega_peredes._ulevaade..pdf
Chang, H.-J. (2003). Kicking away the Ladder: Infant Industry Promotion in Historical Perspective. Oxford Development Studies , 31 (1), 21-32.
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[1] (Gylfason & Hochreiter, 2009)
[2] (Adam, Kristan, & Tomšič, 2009)
[3] Today, 20 years after the break up of SU, Estonia is a member of EU, NATO and OECD but also entered euro-zone and is part of Schengen visa regime. These memberships make Estonia the most integrated country to European structures, among Northern European countries. Today, Estonia is more centrally located to Europe than it has ever been.
[4] Regarding the size of territory, Estonia with its 45,227 km2 can be compared to province Nova Scotia (53,338 km2) in Canada, although population wise Estonian population of 1,3 million compares better with Manitoba (1,2 M).
[5] Even during Soviet times, Western culture was nevertheless influencing Estonia. Finnish communication theorist Terhi Rantanen claims that globalization does take place in closed societies, too (Rantanen, 2001). Soviet audience found their way to non-Communist programs through individual use of videocassettes, she claims. This “outward Westernization” of Soviet Estonia was also experienced via Finnish tourists, Finnish TV and Radio Free Europe/ Radio Liberty and Voice of America. The documentary ‘Disco and Atomic War’ (Kilmi & Aarma, 2009) claims that due to Finnish TV coverage in Estonia, “the Soviet regime went head-to-head with Western pop culture and learned that no one really cared about Lenin or Marx. Instead, the Estonian public wanted to know who shot J.R. and what the latest disco moves are”.
[6] Estonia ranks 29th on Worldwide Corruption Perceptions ranking on 2011, compared to fSU and Eastern Europe countries Estonia is the least corrupt country.
[7] In 1994, Estonia became the first country in Europe to introduce a so-called “flat tax” (The Economist, 2005)
[8] Estonian engineers created the Skype, Estonian government established e-elections, e-government and computer readable ID-card, and set up a Tiger Leap school program of computerization.
[9] Its’ so called “tiger-partners” being geographically distant: in Asia (Asian tigers) and in Ireland (Celtic tiger).
[10] All income data is taken from Gapminder unless otherwise specified.
[11] (It must be mentioned that Estonia succeeded to adopt euro ‘due to prudent fiscal policy, abundant foreign exchange reserves, and capital buffers for the banking sector’ (Deroose, Flores, Giudice, & Turrini, 2010).
[12] Similarly to the GDP and income level, HDI has gone up as well during the transitional period, placing Estonia in the highly developed countries bracket.
[13] Understood as equalized disposable income (Statistics of Estonia)
[14] http://www.oecdbetterlifeindex.org/countries/estonia/
[15] Some academics studying globalization and development[15] would deny that there is a possibility that neoliberal policies could, in the presence of some other favourable conditions as mentioned earlier lead to economic growth[15]. As most Western authors study failure of Structural Adjustment Programs in African countries (and rarely examine countries of former Soviet block or so called Second World) they conclude correctly that (neo)liberal policies caused increase in poverty levels. But Estonian case recommends that in presence of other favourable events, there is an exemption to the rule.
[16] On the other hand, no large scale protests a ‘la Greece took place in Estonia.
[17] Latvia had to be assisted by the European Union, the IMF and other donors (Deroose, Flores, Giudice, & Turrini, 2010)
[18] http://estonia.eu/about-estonia/economy-a-it/a-dynamic-economy.html