Most obviously, it forces students to recognise that major discontinuities in economic performance and economic policy regimes have occurred many times in the past, and may therefore occur again in the future. These discontinuities have often coincided with economic and financial crises, which therefore cannot be assumed away as theoretically impossible. A historical training would immunise students from the complacency that characterised the “Great Moderation”. Zoom out, and that swan may not seem so black after all.
As Robert Solow points out, “the proper choice of a model depends on the institutional context” (Solow 1985, p. 329), and this is also true of the proper choice of policies. Furthermore, the 'right' institution may itself depend on context. History is replete with examples of institutions which developed to solve the problems of one era, but which later became problems in their own right.
Doing economic history forces students to add to the technical rigor of their programs an extra dimension of rigor: asking whether their explanations for historical events actually fit the facts or not. Which emphatically does not mean cherry-picking selected facts that fit your thesis and ignoring all the ones that don't: the world is a complicated place, and economists should be trained to recognise this. An exposure to economic history leads to an empirical frame of mind, and a willingness to admit that one’s particular theoretical framework may not always work in explaining the real world. These are essential mental habits for young economists wishing to apply their skills in the work environment, and, one hopes, in academia as well.
[…]economic history is a rich source of informal theorising about the real world, which can help motivate more formal theoretical work later on.
Monday, July 29, 2013
Wednesday, July 24, 2013
Here is our contribution (co-authored) to a new book on social protection, growth and employment published by the UNDP. It is about the assessment of India’s Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), the national employment guarantee scheme that has already provided employment to over 50 million households. It guarantees a minimum of 100 days a year of paid employment (at state fixed minimum wage rate for unskilled manual labor) to all rural households. More about the program here.
The chapter in the book is an abridged version of an earlier comprehensive assessment(Employing India: Guaranteeing Jobs for Rural Poor) jointly published by Carnegie Endowment and the UNDP.
Below are some of the main points adapted from Chapter 6 (Guaranteeing Jobs for the Rural Poor: An Assessment of India’s MGNREGA Public Works Programme) of the book:
[…]we address the macroeconomic and distributional implications of running an employment generation programme such as the NREGA, including the indirect employment effects it has through its secondary effects on other sectors. Second, we look at the programme’s impact on prices and hence on the cost of living of rural households. Third, we consider the programme’s economic and distributional effects when land productivity increases. Finally, we briefly discuss the extent to which leakages, in the form of hiring non-poor workers, would change the programme’s economy-wide impact, as well as the impact of changing the size of NREGA through a contraction/expansion of its budget.
Overall, the modelling exercise reported in this chapter indicates that, since its inception, the programme has had a positive impact on economic activity beyond the immediate and direct impact of wage payments to the poor people who participate in it. It finds both that the economy as a whole benefits from the programme and also that each major population group does as well. Poor workers in rural areas benefit the most through direct employment creation. Secondary welfare impacts through the creation of demand in other sectors of the economy are larger for higher-income groups than for poor people. In that sense, the programme’s distributional effects are not positive. The impacts are significant yet small due to the programme’s relatively small size in relation to the Indian labour markets. This negative distributional impact, however, is very small and does not modify the programme’s overall progressive redistribution of income in the Indian economy.
[…]Overall programme performance according to the various sources varies significantly according to the specific feature under scrutiny and the geographical location. Independent studies and social audits detail weaknesses and failures, which, although in many cases they raise concerns about the implementation of the programme, also suggest that on the whole it is lowering poverty. The 2009–2010 National Household Survey data confirm that the programme is reaching poor people and is contributing to social inclusion by increasing the participation of deprived social groups and women; it also confirms a strong variance across states in the degree to which the programme accomplishes its objectives.
[…]Given the potentially far-reaching effects of employment generation programmes, economy- wide modelling is a particularly useful tool to analyse their impact in the economy at large. The section below presents the results obtained from an economy-wide model that replicates the characteristics of the NREGA. We identify the beneficiaries according to those defined by the programme, using the coverage and actual composition of workers identified by the programme in 2009–2011, and assuming that the programme only hires low-skilled workers. We also run a separate simulation to look at the impact of an increase in agricultural productivity associated with the implementation of the Act. The data used in this model correspond to a national Social Accounting Matrix (SAM) built for 2003, before the inception of the Act.
[…]We first model an employment generation programme with a budget equivalent to 0.65 percent of GDP, which approximately corresponds to the actual size of the NREGA in fiscal year 2009–2010. The simulation consists of an increase in public expenditures equivalent to 0.65 percent of GDP to hire workers and pay for the necessary materials for construction and the wages of the administrative and few technical staff required by the projects. The simulated increase in public expenditures closely follows the actual composition of the budget in 2009–2010. The payment of wages to workers under the Act is equivalent to 0.43 percent of GDP, expenditures in intermediate inputs are equal to 0.19 percent of GDP, and the payment for government services is equivalent to 0.03 percent of GDP. In proportional terms, 66 percent of programme expenditures go directly to wages for beneficiaries, 5 percent to administration expenses and 29 percent to purchase inputs for the implementation of projects.
In the model we draw labour from rural households in proportions approximating those in the Act in 2009–2010. We assume that the labour hired is divided in equal parts between illiterate male and female workers and that these workers belong to the poorest 60 percent of rural households of SCs and STs and to the poorest 30 percent of households of OBCs and others. The payment of wages to these workers is further inputted into the income of the households from which workers are drawn. The cost of intermediate input materials and administrative expenses, which are assumed to include payments to school- and college-educated workers, represent about one third of the budget, in accordance with the actual budget reported by the programme in the period under consideration.
[…]Results indicate that running an employment generation programme such as the one under the NREGA has a positive macroeconomic impact. An allocation of resources equivalent to 0.65 percent of GDP increases GDP by about 0.4 percent. The programme’s overall expansionary effect is in accordance with the basic notion of a Keynesian balanced budget multiplier, plus the additional demand generated from the shift in income towards poor households with a high marginal propensity to consume.
The programme’s distributional impact is also positive. Simulation results indicate an increase in welfare among poor rural households and a marginal increase among poor urban households. The implementation of the programme carries a cost, which comes in the form of a decline in welfare for rich people in both urban and rural areas, since the programme is financed through income taxes and ‘forced’ savings.
Overall the Act generates an expansion of activity and changes in the composition of production across sectors that result in a progressive redistribution of income towards poor people. The main effects are a sizable redistribution from rich people in urban and rural areas to poor people in rural areas, a marginal redistribution from the same groups to poor people in urban areas and an overall redistribution from urban to rural areas.
[…]Through indirect channels the benefits from the programme extend well beyond its direct beneficiaries. In our simulations, these positive effects extend to 90 percent of the rural population and 30 percent of the urban population. Although the effects are small, partly due to the small size of the programme relative to the size of the Indian labour market, they are nonetheless noticeable.
[…]the increase in labour income triggered by the programme — i.e. the indirect rise in labour income — is in the order of 0.11 percent. The small size of this effect is mainly because the direct wage payments of the programme represent no more than 8 percent of the total income earned by illiterate workers and 2 percent of the total annual income of the rural labour force. This result serves as a reminder that, as impressive as the NREGA programme is, it is still a small fraction of labour income in India.
[…]The simulated 1.5 percent increase in land productivity produces an appreciable rise in GDP, final demand and trade, ranging between 0.02 and 0.03 percent. The increase in agricultural productivity has a less positive impact on income distribution. Although the rise in productivity increases welfare across all household groups, the increase is larger for rich people and larger in urban than in rural areas.
[…]The effect on prices is so strong that even if the productivity hike decreases poor people’s income and, hence, consumption expenditures, the fall in the price of food implies such a strong rise in purchasing power that they end up better off than before. After the increase in productivity, poor people can buy more food and perhaps even increase purchases of other goods.
[…]Our simulation increasing land productivity has the expected result of expanding economic activity and enhancing aggregate welfare. It increases welfare and consumption expenditures across all households, both rural and particularly urban, and it amplifies activity in the agriculture, food-processing and service sectors.
[…]In the simulation results, however, increasing productivity also has a negative distributional impact due to a larger increase in the welfare of rich households. This result is driven by the high concentration of land in the hands of rich people. This result should not be interpreted as a criticism of the important objective of programmes such as the NREGA to increase productivity in agriculture.
[…]Our analysis suggests that the effects of leaks do not visibly change the programme’s macroeconomic impact. The presence of leakage in the implementation of a programme such as the NREGA should not be a major concern for policy makers considering its macroeconomic and distributive effects.
Wednesday, July 17, 2013
Finance Minister Shanker Prasad Koirala introduced a timely and full budget for FY2014 on Sunday. Shunning populist slogans, programs and policies, the budget prioritized hydropower and energy development; agriculture productivity and commercialization; physical infrastructure development; access to social education, health, drinking water and sanitation; tourism development; investor-friendly environment; export promotion; and good governance.
FY2014 budget targets
|GDP growth (%)||5.5|
Budget allocation for FY2014
|Projected total revenue||429.5||100|
|Budget surplus (+)/deficit (-)||-87.7|
The total budget for FY2014 is Rs 517.2 billion, with Rs 353.4 billion for recurrent expenditures, Rs 85.1 billion for capital expenditures, and Rs 78.7 billion for financial provision. The total budget allocation for FY2014 is 27.8% higher than FY2013 budget allocation and 41.1% higher than the revised estimate of total expenditure in FY2013.
The projected total revenue is Rs 429.5 billion, with 82.5% of it coming from tax revenue, 16.2% from foreign grants, and 1.3% from principal repayment. This leaves the government with Rs 87.7 billion of budget deficit, whose financing would come from foreign loans and domestic borrowing of 49.8% and 50.2%, respectively, of the deficit.
The table below provides income and expenditure snapshot of the FY2014 budget and the FY2013 revised estimate. Due to the lack of timely full budget and the inability to spend allocated money in time along with high revenue mobilization, there was net savings in FY2013.
|FY 2014 budget targets||FY2014 BE||FY2013 RE|
|GDP growth target (%)||5.5||3.6|
|Inflation target (%)||8||9.9|
Income and Expenditure FY2014
|Rs billion||Rs billion|
|Projected total expenditure||438.5||311.7|
|Projected total revenue||424.0||337.6|
|Surplus (-)/deficit (+)||14.5||-25.9|
|Net loan investment||24.5||12.8|
|Net share investment||7.2||9.3|
|Net foreign loans||-27.4||-0.7|
|Net domestic borrowing||-18.8||-2.0|
Some macro related points to consider (for more, see Economic Survey 2013 as well):
- Recurrent expenditure allocation is really high. It is barely equal to tax revenue target. The growth in FY2014 budget allocation (BE) is 40.7% over FY2013 revised estimate (RE). Rationalization of recurrent expenditures has to be thought of seriously. Grants to local bodies and social service constitute 42% of recurrent expenditure, followed by compensation of employees (25%), use of goods and services (15%), and social security (15%). The allocation for compensation of employees, use of goods and services, grants, and social security increased by 30.4%, 88.3%, 40.6%, and 12.9%, respectively, compared to the revised estimate of respective expenditures in FY2013.
Note: FY2014 nominal GDP at producers’ prices assumed to be 14.7% (average of FY2012 and FY2013) higher than FY2013 provisional data. Revised estimate of revenue in FY2013 is higher than revised estimate of expenditure because of the inability of the government to spend the allocated budget in time, thanks to the lingering political uncertainties and delay in bringing out a timely and full budget.
- Capital allocation has remained around 16.5% of budget allocation, but problems always arise during implementation. More challenges would prop up both scale and quality fronts in the run up to the CA elections (and possibly local body elections).
- Revenue target is 20% in FY2014, down from 21% between FY2013RE and FY2012. Given the weakening currency and a potential slowdown in imports (due to depreciation, but we will have to see remittances growth to see the net impact), revenue target might be challenging. The existing reforms have to be sustained and its reach expanded to increase tax net and tax base.
- Allocation for financial provision has been equal to or higher than capital expenditure. It includes internal loan investment, domestic share investment, and external (borrowing) amortizations and domestic (borrowing) amortization. This probably has direct relationship with the government’s continuous pumping in of money in public enterprises (last year only 2 of the 37 PEs gave dividends and 21 operated in losses) as well as high debt servicing as a result of higher borrowing. The combined loss of NOC and NEA was Rs 19.5 billion (1.27% of GDP in FY2012).
- Domestic borrowing is getting larger than external borrowing. Interest on domestic borrowing (except for T-bills) is higher than interest on concessional loans from multilateral banks because the interest rate is usually pre-determined (much higher than market rates) before auction. Higher domestic borrowing might also impact liquidity situation in the banking sector. As a share of estimated FY2014 GDP, planned deficit financing is about 4.5% of GDP (2.2% of GDP foreign loans, and 2.3% of GDP domestic borrowing).
- Growth target is ambitious and inflation target is conservative. The recent depreciation of the rupee (except against Indian rupee) might dampen not only revenue mobilization, but also exert pressures on prices as more than 50% weight in CPI index comes from non-food and services, which are mostly imported. Also, market prices will see upward pressures coming from the hike in salary and allowance of public employees. It is mostly going to be ‘push’ factors, complemented by the persistent supply-side constraints.
The blocks refer to the share of functional expenditure in total expenditure (including financing). The numbers (in Rs ‘000) is the amount of budget allocation or expenditure.
The blocks refer to the share of expenditure item in total economic affairs functional expenditure heading. The numbers (in Rs ‘000) is the amount of budget allocation or expenditure.
Sunday, July 14, 2013
The Finance Ministry has published Economic Survey 2012/13. One of the most interesting things in economic survey each year is that it reports the progress on several economic and development fronts (though the latest stats do not cover the entire 12 months of the running year).
The real sector data comes from the CBS, which usually publishes provisional figures well before the economic survey is published. The Central Bureau of Statistics (CBS) released its annual national account estimate on 5 April 2013, projecting GDP at basic prices to grow at 3.56%, down from 4.48% revised estimate for FY2012 (fiscal year ends on 15 July). The CBS projects services sector to grow by 6.03%, industry sector growth to further drop to 1.49%, and agriculture sector to grow by a mere 1.31%.
The sharp drop in agriculture growth is attributed to the unfavorable monsoon and shortage of chemical fertilizers during peak paddy planting season. The industry sector continues to be beset by persistent supply-side as well as structural constraints, including power outages, labor disputes, low productivity, high cost of raw materials and production, inadequate investment climate reforms, lack of innovation and research and development, corruption, and political instability. High services sector growth is supported by demand backed by high remittance inflows.
|GDP growth rate (basic prices)||3.85||4.48||3.56|
|Composition of GDP (%)|
Some useful stats (provisional) from the ES (FY2013):
Real sector (GDP growth has declined; domestic savings are down but national savings are up due to high inflow of remittances; so is per capita GNDI)
- Per capita GDP: US$717
- Per capita GNI: US$721
- Per capita GNDI: US$926
- Gross domestic savings: 9.3% of GDP
- Gross national savings: 38.4% of GDP
- Gross fixed capital formation: 21.2% of GDP
- Total population: 27.2 million
- Inflation: 10.6%
Fiscal sector (revenue growth has declined; government expenditure growth has increased; tax revenue has increased; budget deficit is up; external loans are up)
- Revenue growth: 18.5%
- Revenue: 17% of GDP
- Tax revenue: 14.8% of GDP
- Government expenditure: 23.8% of GDP
- Budget deficit: 3.7% of GDP
- Domestic borrowing: 2.2% of GDP
- External loan: 1.5% of GDP
- Public debt: 30.1% of GDP
- Outstanding domestic debt: 12.4% of GDP
- Outstanding external debt: 17.6% of GDP (or 103.6% of revenue; 587% of exports)
Monetary sector (total credit growth down; growth of credit to private sector up; money supply decreased)
- Total credit growth: 8.9%
- Growth of credit to private sector: 15.6%
- Money supply (M2) growth: 6.2%
- Total loans: 63.7% of GDP
- Total loans to private sector: 55% of GDP
- Money supply: 70.6% of GDP
External sector (export growth down; import growth up; trade deficit up; tourism income growth down; remittance income growth down; current account surplus down; balance of payments surplus down)
- Merchandise export growth: 4.2%
- Merchandise import growth: 20.4%
- Merchandise trade deficit growth: 23.5%
- Merchandise export: 4% of GDP
- Merchandise import: 29% of GDP
- Merchandise trade deficit: 24.9% of GDP
- Tourism income growth: 4%
- Tourism income: 1.7% of GDP
- Remittances growth: 19.6%
- Remittances: Rs 430 billion (22.4% of GDP)
- Current account balance: 1.4% of GDP
- Balance of payments: Rs 11.8 billion
- Foreign exchange reserve: Rs 453.6 billion (10.2 months of goods import or 8.7 months of import of goods and non factor services).
The annual comparison is more revealing when the full year fiscal sector, monetary sector and external sector data are released around end of August. Right now, the data is good to observe any interesting as well as alarming trends.
Performance of public enterprises (PEs) in FY2012:
- Of the 37 PEs, 15 made profit and 21 made loss. One did not do any transaction. 8 PEs that earned profit last year made losses this year.
- Total loss incurred by PEs reached Rs 3.49 billion in FY12, compared to profit of Rs 6.69 billion recorded a year earlier.
- NOC and NEA reported loss of Rs 9.52 billion and Rs 9.94 billion, respectively, in FY2012. Combined loss is 1.27% of GDP in FY2012.
- The government has recently decided to pay off the staff of Janakpur Cigarette Factory (Rs 2 billion needed) and is considering doing the same at Nepal Drugs Company in order to liquidate them.
- Pension related obligations increased by 25.9% to Rs 21.2 billion from Rs 16.8 billion a year earlier.
- Political interference and growing unionization are eroding competitiveness
- Excess number of staff needs to be downsized and productivity boosted to remain relevant and financially afloat.
Wednesday, July 10, 2013
- Hydro and other energy development
- Agriculture productivity, diversification and commercialization
- Road and other physical infrastructures
- Social sector: basic education, health, drinking water and sanitation
- Tourism, industry and trade
- Good governance
Friday, July 5, 2013
[…]sudden hikes in interbank rates – which clearly indicate credit tightness in the banking sector -- could precipitate a decline in private sector investment, make the banking and financial sector unstable, and eventually affect the real economy.
[…]commercial banks need to maintain a capital buffer -- known capital adequacy ratio -- of 10 percent. These ratios -- which are measures of the amount of capital held by banks and financial institutions in relation to risk-weighted credit exposures -- stand at 11 percent for development banks and finance companies.
[…]these buffers ultimately protect the interest of depositors, who park hard-earned money in banking institutions, and prevent financial risks from building up in the country’s banking system.
[…]however, the level of these buffers at banks and financial institutions has been gradually declining. The average capital adequacy ratio of commercial banks stood at 11.30 percent as of mid-April, according to Nepal Rastra Bank’s latest report. Although the figure shows holding of an extra 1.30 percentage points of capital fund by commercial banks, the discomforting part is the regulator’s instruction to maintain a capital buffer of at least 11 percent to be able to distribute cash dividend to shareholders.
[…]banks are currently operating with very little extra capital, which is constricting their ability to lend.
[…]Although one may argue there is not much credit demand these days due to the not-so-encouraging investment climate, banking institutions will gradually need to stimulate lending to meet the country’s target of attaining a seven percent growth rate till 2022 to graduate from the category of least developed country to developing country. And data shows there is ample room for credit expansion, as lending of banks and financial institutions as a percentage of GDP currently stands at only 59.2 percent.
[…]if the regulator asks banks to raise paid-up capital to, say, Rs 5 billion within the next three years, and to Rs 10 billion within next seven years, then this technique might not work for all, as many may not be able to earn such huge profits in such a short period of time.
[…]other options for raising capital, such as, asking promoters to inject cash, mergers, or leveraging -- that is issuing corporate bonds.
[…]Currently, many promoters are not as enthusiastic about putting money from their own pockets as return on equity is gradually declining. At the end of the third quarter of the current fiscal year, the average annualized return on equity of commercial banks stood at 14.75 percent as against around 20.66 percent around three years ago. This is because of fierce competition.
[…]This leaves banks and financial institutions with the only option of merger to raise capital, which is probably the fastest way of meeting the minimum regulatory capital requirement.
[…]merger of institutions with very little free capital would only expand the balance sheet size of the consolidated units without addressing the problems that can raise the specter of credit crises and ultimately destabilize the financial sector and the economy.
[…]This, however, does not mean mergers are ineffective in solving many problems faced by banking institutions, as they can expand single obligor limit that allows lenders to give bigger-sized loans to single parties. Mergers can also reduce operating cost, including fixed costs like salaries.
For a brief note on the financial sector vulnerability, see the policy challenge section of Asian Development Outlook 2013 Nepal chapter.
Tuesday, July 2, 2013
Based on the recent household surveys and census data, the CBS has come up with Small Area Estimation of Poverty 2013 in Nepal. A general trend is that while the (rural) Far West and Mid West districts have the highest proportion of population living below the poverty line, the Terai districts have the highest number of poor people below the poverty line. The poverty line is fixed at Rs 19,261 (both food and non-food).
According to the latest figures, Bajura has the high percentage of district population (64.1%) living below the poverty line, followed by Kalikot (57.9%), Bhajhang (56.8%), Humla (56%) and Darchula (53%). The districts with the least proportion of poor as a share of the respective district’s population are Kaski (4%), Illam (7.3%), Lalitpur (7.6%), Kathmandu (7.6%) and Chitwan (8.9%). Note that at the national level, the poverty rate is 25.2% of the total population.
Now, do not get confused with the percentage of poor with the number of poor. For instance, while poverty rate in Bajura is 64.1% of that district’s population (134,062), the number of poor people below the poverty line is 85,934. Similarly, while Kathmandu has poverty rate of 7.6%, the number of poor people in Kathmandu is 128,298.
Overall, Nepal has 6,588,664 number of poor people living below the poverty line (25.16% of 26,187,059 = 6.59 million). Kailali has the highest number of poor (257,204), followed by Saptari (251,643), Rautahat (227,340), Siraha (219,656), and Bara (203,348). The least number of poor people are in Manang (2,150), Mustang (4,634), Rasuwa (13,311), Terhathum (147,17), and Dolpa (184,98).
Comparing the progress between 2001 (based on NLSS II) and 2011 (based on NLSS III), the data shows that poverty (% of respective district population) declined in 55 districts, but increased in 19 districts. Twenty districts were able to reduce poverty by over 20 percentage points.
The largest reduction in poverty happened in Panchthar (down from 52.5% in 2001 to 11.4% in 2011 = 41.1 percentage points), followed by Rolpa, Illam, Dhankuta and Khotang. Poverty increased the most in Bajura (by 16.8 percentage points), followed by Manang, Darchula, Jumla and Humla. While Kathmandu and Bhaktapur saw increase in poverty by 3.2 and 3.8 percentage points, respectively, Lalitpur saw a decline in poverty by 2.5 percentage points.
Now, the following comparison (at the district level) will be interesting. I will try to write separate blog posts when I have more free time as these tend to have growth and development policy implications:
- Percentage point decline in poverty, and remittance inflows and per capita remittance receipts
- Percentage point decline in poverty and migration/absentee population
- Percentage point decline in poverty and changes in education and health services
- Percentage point decline in poverty and aid concentration
- Percentage point decline in poverty and per capita public expenditure
- Percentage point decline in poverty and provision of infrastructure (electricity, roads, telephone)
- Percentage point decline in poverty and change in real estate and housing prices
- Percentage point decline in poverty, and agriculture production and agriculture productivity
- Percentage point decline in poverty and industrial value added production
More on these and poverty gap and poverty severity by district in later posts.