Thursday, December 18, 2014

New paper: Inclusive Economic Growth in Nepal

Below is the abstract of a recent paper published in Journal of Poverty Alleviation and International Development, Vol.5, No.2, pp.77-116 (authored by yours truly!) :) 

Inclusive economic growth is one of the most prominent development agendas. However, a systematic evaluation of progress toward greater inclusivity in the developing countries, and the required strategic foci for the future, remain largely absent from debates in both the academic and policymaking spheres. This paper applies and complements the Asian Development Bank’s inclusive economic growth framework by including an intra-country analysis, and in particular, the convergence and divergence across a range of relevant indicators among consumption quintiles in Nepal. It finds three stark disparities: (i) Nepal’s GDP growth and per capita growth remain the lowest in South Asia; (ii) the slow growth rate has failed to create adequate job opportunities, resulting in large-scale out-migration of workers from all consumption quintiles; and (iii) despite the overall inclusive pattern of growth over the last decade, there remains large disparities in the reach and utilization of social services and economic opportunities among the poorest quintiles. In addition, the pattern of growth could be made more inclusive by creating new opportunities and ensuring that the existing ones are shared more proportionately with the bottom quintiles.

Wednesday, December 17, 2014

Illicit financial outflows from Nepal over 2003-2012

A latest report from Global Financial Integrity (GFI) ranks Nepal 68 out of 145 economies in terms of average annual illicit financial flows— the cross-border movement of money that is illegally earned, transferred, or utilized— over 2003-2012. On an average, from Nepal, between 2003 and 2012, US$755 million was illegally earned, transferred, or utilized.

Illicit financial outflows has drastically reduced lately, largely due to lower import over-invoicing. In 2012, Nepal ranked 102 out of 151 economies, with illicit financial outflow equivalent to US$106 million. Here is an earlier blog post on previous reports. Illicit capital flows are detected by analyzing misinvoicing of external trade transactions and leakages from the balance of payments.

Cumulative illicit hot money outflows and trade misinvoicing were equivalent to US$228 million and US$7,254 million, respectively. Total illicit outflows between 2003 and 2012 was US$7,542 million. The largest illicit outflows came from trade misinvoicing (export over-invoicing and import over-invoicing). Import under-invoicing and export under-invoicing were not recorded. Over 2003-2012, cumulative import over-invoicing and export over-invoicing were US$7.254 billion and US$1.451 billion, respectively. This might be one of the reasons for the sudden slowdown in the growth of remittances in recent months of FY2015. Any downward trend in the growth of remittance inflows creates far reaching ripple effects across all sectors (real, fiscal, monetary and external).

Over-invoicing imports is common and is mostly attributed to high taxes (reduces corporate profits) and incentives to benefit from foreign exchange transaction in the black market. Over-invoicing exports is not that common and is mostly done to receive higher government subsidies (like in the case of cash incentives for exports).

In South Asia, India saw the largest illicit financial outflows, followed by Bangladesh, Pakistan, Sri Lanka, the Maldives, Bhutan, and Nepal. Overall, US$991.2 billion flowed illicitly out of developing and emerging economies in 2012.

Illicit financial outflows (HMN+GER), US$ million
Country 2008 2009 2010 2011 2012
Afghanistan  0 0 0 0 0
Bangladesh 1,229 1,063 672 593 1,780
Bhutan 0 0 0 44 168
India 47,179 29,002 70,236 86,002 94,757
Maldives 55 38 62 69 185
Nepal 854 1,551 1,883 645 106
Pakistan 51 0 729 0 405
Sri Lanka 0 0 881 337 349

Illicit/unrecorded money moves across borders under the following three forms:

  • Corrupt: Proceeds of bribery and theft by government officials
  • Criminal: Proceeds of drug trading, human trafficking, counterfeiting, contraband, and myriad forms of additional activities
  • Commercial: Proceeds arising from import and export transactions conducted so as to manipulate customs duties, VAT taxes, income taxes, excise taxes, or other sources of government revenues

Here is how GFI computes the illicit flows:

In analyzing illicit financial flows (IFFs), GFI utilizes sources of data and analytical methodologies that have been used by international institutions, governments, and economists for decades. Basically, these data sources and methodologies are providing information on gaps—gaps in balance of payments data and gaps in trade data. Where recorded sources and uses of funds in balance of payments data do not match, the difference is net errors and omissions, indicating an inflow or outflow that was not recorded. Where bilateral trade data does not match (after adjusting for freight and insurance in the data of the importing country) this indicates re-invoicing of transactions between export from one country and import into another country.

GFI recommends countries to:

  • Comply with all of the Financial Action Task Force (FATF) Recommendations to combat money laundering and terrorist financing
  • Require meaningful confirmation of beneficial ownership in all banking and securities accounts
  • Automatic exchange of financial information
  • Require multinational corporations to publicly disclose their revenues, profits, losses, sales, taxes paid, subsidiaries, and staff levels on a country-by-country basis, as a means of detecting and deterring abusive tax avoidance practices
  • Boost customs enforcement by equipping and training officers to better detect the intentional misinvoicing of trade transactions (it accounts for 77.8% of all illicit flows).

Sunday, December 14, 2014

Impact of inequality or equality on growth…it depends

Dani Rodrik on inequality: there is no universal evidence that inequality jeopardizes growth (alternatively, equality supports growth). It all depends on other supporting factors (the root causes may not be known or cannot be factored in econometric analysis), and there is no iron law.

Excerpts from the article:

The belief that boosting equality requires sacrificing economic efficiency is grounded in one of the most cherished ideas in economics: incentives. Firms and individuals need the prospect of higher incomes to save, invest, work hard, and innovate. If taxation of profitable firms and rich households blunts those prospects, the result is reduced effort and lower economic growth. Communist countries, where egalitarian experiments led to economic disaster, long served as “Exhibit A” in the case against redistributive policies.

In recent years, however, neither economic theory nor empirical evidence has been kind to the presumed tradeoff. Economists have produced new arguments showing why good economic performance is not only compatible with distributive fairness, but may even demand it.

For example, in high-inequality societies, where poor households are deprived of economic and educational opportunities, economic growth is depressed. Then there are the Scandinavian countries, where egalitarian policies evidently have not stood in the way of economic prosperity.

[…]Economics is a science that can claim to have uncovered few, if any, universal truths. Like almost everything else in social life, the relationship between equality and economic performance is likely to be contingent rather than fixed, depending on the deeper causes of inequality and many mediating factors. So the emerging new consensus on the harmful effects of inequality is as likely to mislead as the old one was.

Consider, for example, the relationship between industrialization and inequality. In a poor country where the bulk of the workforce is employed in traditional agriculture, the rise of urban industrial opportunities is likely to produce inequality, at least during the early stages of industrialization. As farmers move to cities and earn higher pay, income gaps open up. And yet this is the same process that produces economic growth; all successful developing countries have gone through it.

In China, for example, rapid economic growth after the late 1970s was associated with a significant rise in inequality. Roughly half of the increase was the result of urban-rural earnings gaps, which also acted as the engine of growth.

Or consider transfer policies that tax the rich and the middle classes in order to increase the income of poor households. Many countries in Latin America, such as Mexico and Bolivia, undertook such policies in a fiscally prudent manner, ensuring that government deficits would not lead to high debt and macroeconomic instability.

[…]It is good that economists no longer regard the equality-efficiency tradeoff as an iron law. We should not invert the error and conclude that greater equality and better economic performance always go together. After all, there really is only one universal truth in economics: It depends.

Monday, December 1, 2014

Labor productivity and structural transformation in Nepal (plus LDCs)

The latest LDC Report 2014 focuses on the linkages between structural transformation, economic growth and human development. It argues that economic growth “must be accompanied by structural transformation and the creation of decent jobs in higher-productivity activities”. It has came up with a new term: "LDC paradox", which refers to “the failure of the MDGs to recognize the need for a policy framework that generates transformative growth, and in the inability of the LDCs to achieve structural transformation”.

The report underscores that the post-2015 agenda (Sustainable Development Goals) should focus on structural transformation of LDCs towards a modern and diversified economy (higher value-added sectors and more knowledge-intensive activities) in order to reverse the decline in labor productivity and to increase employment. It recommends three specific policy measures:

  • Resource mobilization (to generate financing for productive public and private investment)
  • Industrial policy (to direct those resources into sectors and activities that promote structural transformation)
  • Prudent macroeconomic framework/policies(to support structural transformation rather than impeding it— mainly, public investment, credit, real exchange rate, and domestic demand)

Labor productivity growth is a crucial factor in determining the pace and pattern of economic growth— essentially a structural transformation (changes in composition of output, employment, exports and aggregate demand). Labor productivity is generally higher in countries that export more manufactured and mixed goods— reflective of the structure of the economies they have. Countries with sluggish growth tend to export more food and agriculture products.

Economic performance is based on two interrelated processes: labor productivity and structural change. Labor productivity growth is determined by: (i) innovations within sectors (increases in capital, new technology and knowledge), and (ii) shift of labor across sectors (from lower to higher productivity activities). Labor productivity growth can be decomposed into growth of labor productivity by sector and the growth of employment (demographic and labor market components).

For countries like Nepal economic growth should be characterized by a dynamic transformation of sectors and employment share— as opposed to the growth being propped up by monsoon rains and remittance-induced demand for imported goods. Nepal needs to boost productivity within sectors (shifting from lower value added agriculture and services activities to higher value added activities within the sectors), and productivity across sectors (shifting production/employment structure from agriculture to industry before jumping into services sector— this is the proven path for sustained rise in income per capita).

The report decomposes aggregate labor productivity into three main components:

  • Direct productivity growth effect (changes in aggregate output per sector due to increases in productivity within sector)
  • Structural/reallocation effect (changes due to movements of labor between sectors with different levels of output per capita)
  • Terms-of-trade effect (changes due to relative output prices between sectors)

Manufacturing sector is important for higher productivity gains emanating from intersectoral reallocation of labor. Also, higher aggregate output per worker is strongly associated with higher productivity in the industrial sector, and with the transfer of workers to this sector.

Here is how Nepal stands relative to other LDCs in South Asia (and People’s Republic of China, which is not a LDC but has transformed is economy drastically within a generation’s time): 

  • Productivity gains within sectors contributed more to aggregate labor productivity growth than structural effect (this is expected because due to the lack of domestic employment opportunities there is a large-scale out migration of workers each year, contributing workers’ remittances equivalent to about 28% of GDP, which finance either the imported goods traded in services sector or nontradable activities within the sector). Bhutan had more productivity growth coming from structural/reallocation effect because of the large shift of workers to industry sector (electricity falls under this) after the hydropower boom.
  • Nepal’s labor productivity growth is low compared to the regional economies (see the dots in the above chart) .
  • In direct productivity growth effect and reallocation effect, services sector contributed the most.
  • Relocation effects in agriculture is negative, reflecting its reduced share in employment because of the shift of workers to other high productivity sectors. It shows trade-offs between employment generation and labor productivity (inverse).
  • The highest level of employment growth is registered in services sector. However, these are mostly informal in nature with severe lack of productive capacities at the firm level (low level of capital and information technology). Employment growth in services sector is broadly at the expense of gains in labor productivity. The reallocation effects (agriculture to services sectors) added to overall productivity growth because average productivity is higher in services sector (even if underemployment is high).
  • Industry sector productivity (both within and across) is considerably low (most probably due to the crippling binding supply-side constraints).

More on structural transformation in Nepal here (interested folks can follow the links within the blog post as well). Briefly, Nepal has ended up with an unusual structural transformation. Most of the GDP growth is coming from non-tradable sectors such as construction, retail and wholesale trade and real estate and housing. The demand for the services sector activities are in turn driven by public expenditure and remittances (see the rise in services sector value added while a premature deindustrialization in the chart below). Tradable sectors such as manufacturing and high-value agriculture activities are not prominent. Worse, more and more workers are shifting to informal activities in services sector until they find jobs overseas. Addressing this will be one of the major economic challenges for the Constituent Assembly II, if the country wants to realize its goal of graduating from LDC status by 2022.

Friday, November 28, 2014

Highlights of the 18th SAARC Summit Declaration

The 18th SAARC Summit was held in Kathmandu on 26-27 November 2014. The most prominent regional feature was the agreement on the framework on energy cooperation. Motor vehicles and regional railways agreements are to be finalized within three months.

Excerpts from the declaration:
  • Commitment to achieve South Asian Economic Union (SAEU) in a phased and planned manner through a Free Trade Area, a Customs Union, a Common Market, and a Common Economic and Monetary Union
  • Effectively implement the existing preferential facilities under SAFTA and SATIS (especially for Least Developed and Landlocked Member States)
  • Accelerate free trade in goods and services in the region putting into operation simplified and transparent rules of origin; implementation of trade facilitation measures; harmonization of standards relating to Technical Barriers to Trade (TBT) and sanitary and phyto-sanitary measures; harmonized, streamlined and simplified customs procedures; elimination of non-tariff and para-tariff barriers; and smooth and efficient transit and transport facilities
  • Signing of the SAARC Framework Agreement for Energy Cooperation (Electricity)
  • Identify regional and sub-regional projects in the area of power generation, transmission and power trade, including hydropower, natural gas, solar, wind and bio-fuel, and implement them with high priority with a view to meeting the increasing demand for power in the region
  • Initiate an Inter-Governmental process to appropriately contextualize the Sustainable Development Goals (SDGs) at the regional level
  • Eliminate the threshold criteria from the SAARC Food Bank Agreement so as to enable the Member States to avail food grains, during both emergency and normal time food difficulty
  • Collaborate and cooperate on safe, orderly and responsible management of labour migration from South Asia to ensure safety, security and wellbeing of their migrant workers in the destination countries outside the region
  • India to develop and launch a satellite dedicated to SAARC Countries
  • Collaboration and engagement among public authorities and private stakeholders in the Member States to lower telephone tariff rates for facilitating greater contacts among the people of the region and called for rationalization of the tariff structures
  • Effectively implement SAARC Action Plan on Tourism (2006) particularly through initiating appropriate public-private collaboration
  • Hold henceforth the meetings of the SAARC Summit every two years or earlier
Meanwhile, Nepal and India signed 12 agreements/MoUs on the sidelines of the summit. These include:
  • MoUs on tourism, traditional medicines and youth exchange
  • Motor Vehicle Agreement
  • MoU on PDA for Arun III
  • Twin City Agreements between Ayodhya-Janakpur, Kathmandu-Varanasi, and Lumbini-Bodh Gaya

Friday, November 14, 2014

Historical path and growth forecast: Regression to the mean

Lant Pritchett and Lawrence Summers argue that growth forecasters should taken into account the potential of a slowdown in China and India, especially their growth averaging towards the mean based on both internal (institutions) and external conditions (commodity prices, climate change, geopolitics, etc).

Excerpts from the paper:

Regression to the mean is the single most robust finding of the growth literature, and the typical degrees of regression to the mean imply substantial slowdowns in China and India. relative even to the currently more cautious and less bullish forecasts.

India and, even more so, China are experiencing historically unprecedented episodes of growth. China’s super-rapid growth has already lasted three times longer than a typical episode and is the longest ever recorded. The ends of episodes tend to see full regression to the mean, abruptly.

It is impossible to argue that either China or India has the quality institutions that have been associated with the steady dynamic of growth in the currently high productivity countries. The risks of sudden stops are much higher with weak institutions and organizations for policy implementation. China and India have very different modalities of this risk, but both have tricky paths to continued prosperity.

We suggest several implications of these conclusions. First, there will be a strong tendency to assume that, if growth slows substantially in China or India, it will represent an important policy failure. This is not right. Regression to the mean in a decade or so is the rule, not the exception. What would require much more explanation would be continued rapid growth, which would be very much outside the general run of experience. Second, those making global projections should allow a very wide confidence interval with respect to growth for countries whose current growth rates are far from the mean. Given the sensitivity of commodity demands in particular to growth rates in Asia, this suggests substantial uncertainty about the medium-term path of commodity prices. In the same way, forecasts of global energy use and climate change impacts should also recognize the possibility of discontinuities in Asia. Third, much geopolitical analysis has focused on the implications of a rising China, and certainly Chinese international relations theorists have extensively studied past rising powers. Contingency planning should also embrace scenarios in which Chinese growth slows dramatically, presumably bringing with it a range of domestic and international political implications.

Saturday, November 8, 2014

Minimum wage and productivity in Nepal and South Asia (plus China)

Here is an update on the minimum wage and labor productivity in South Asia (plus China). In 2012, in a series of blog posts (here and here— also, here and here), I indicated that the minimum wage in manufacturing sector in Nepal is the highest in South Asia. The latest updated data (sourced from DB2015) shows India’ and Pakistan’s minimum wages above Nepal’s.

At US$95 per month in 2014, the minimum wage in Nepal was the third highest in South Asia. The minimum wage in India and Pakistan was $142 per month and $110 per month, respectively. In 2012, Nepal had the highest minimum wage in South Asia. Minimum wage in Nepal has drastically increased from $32.3 in 2007— a 194% growth over 2007-2014.

Relative to Nepal’s level (=100 in the chart below), minimum wages in China, India, and Pakistan are higher. Sri Lanka had higher minimum wage than Nepal in 2013.

However, productivity has not kept pace with the increase in minimum wage. Compared to 2007, labor productivity (measured by the ratio of minimum wage to value added per worker – not a perfect indicator, but its okay for indicative purpose!) in Nepal decreased by 18%. In fact, India and Pakistan also saw a decline in labor productivity over the same period. Sri Lanka and China saw increase in labor productivity. The ratio of minimum wage to value added per worker in 2007 was 0.8, which increased to 0.9 in 2014 (a higher value indicates lower labor productivity). Note that value added per worker is also affected by quantity and quality of other inputs, particularly raw materials and physical and social infrastructures (electricity, transport, educated workforce, healthcare, etc). The average value added per worker is the ratio of an economy’s GNI per capita to the working-age population as a percentage of the total population.

Nepal’s labor productivity is the lowest in South Asia. The chart below shows South Asia’s (plus China’s) labor productivity relative to Nepal’s in 2013 and 2014. All of them have better productivity than Nepal’s. India’s and Nepal’s labor productivity seems to be converging lately. This opens up an opportunity to relocate manufacturing firms to Nepal as wages are lower here and productivity is pretty much similar. IF the other inputs listed above are reasonably supplied in Nepal (plus reasonable degree of political stability), there is no reason to doubt that an increasing number of firms may opt to base their manufacturing plants here.

Lower (competitive) wages and higher labor productivity attract domestic and foreign investment, which help to boost jobs creation and economic growth. Nepal’s formal sector labor market suffers from a high degree of unionism (often politically motivated and at times violent), which has resulted in the closure of many domestic as well as multinational firms. Overall, manufacturing sector has been weakening over the past several years. Its share of GDP declined to an estimated 5.6% in FY2014 from 8.2% of GDP in FY2002. The average growth rate has been a mere 3.2% in the last five years. Here is a related blog post on this issue.