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As a small and open economy, Belarus' development perspectives are intrinsically linked to its ability to produce and sell goods and services competitively in the global marketplace. While Belarus is an open economy, its trade links are concentrated both in terms of products and markets. Mineral goods –most importantly refined oil and potassium chloride - are the main export product accounting for more than 1/3 of total exports. Non mineral exports, including most importantly machinery, vehicles and transport equipment are mostly exported to Russia and other CIS markets, which account for 74 percent of non-mineral exports while the share of EU countries in Belarus non-mineral exports account for less than 15 percent. With Russia's WTO accession in 2012 competitive pressures on Belarus’ major market for non-mineral exports have further intensified. As Belarus is accelerating its own negotiations with the WTO, understanding the challenges and opportunities faced by the country's exporters is critical to putting in place an effective adaptation strategy that will enhance competitiveness and ensure Belarus can take full advantage of more open market access. The objective of this note is to analyze the economic impacts of Belarus' potential accession to the WTO. The note utilizes a modern computable general equilibrium model of the economy of Belarus to simulate impacts on the economy as a whole and on individual sectors.

This paper uses a large national household panel from 1999/2000 and 2007/08 to analyze the short-term effects of India's Mahatma Gandhi National Rural Employment Guarantee Scheme on wages, labor supply, agricultural labor use, and productivity. The scheme prompted a 10-point wage increase and higher labor supply to nonagricultural casual work and agricultural self-employment. Program-induced drops in hired labor demand were more than outweighed by more intensive use of family labor, machinery, fertilizer, and diversification to crops with higher risk-return profiles, especially by small farmers. Although the aggregate productivity effects were modest, total employment generated by the program (but not employment in irrigation-related activities) significantly increased productivity, suggesting alleviation of liquidity constraints and implicit insurance provision rather than quality of works undertaken as a main channel for program-induced productivity effects.

This paper presents a model to assess the socioeconomic resilience to natural disasters of an economy, defined as its capacity to mitigate the impact of disaster-related asset losses on welfare, and a tool to help decision makers identify the most promising policy options to reduce welfare losses due to floods. Calibrated with household surveys, the model suggests that welfare losses from the July 2005 floods in Mumbai were almost double the asset losses, because losses were concentrated on poor and vulnerable populations. Applied to river floods in 90 countries, the model provides estimates of country-level socioeconomic resilience. Because floods disproportionally affect poor people, each $1 of global flood asset loss is equivalent to a $1.6 reduction in the affected country's national income, on average. The model also assesses and ranks policy levers to reduce flood losses in each country. It shows that considering asset losses is insufficient to assess disaster risk management policies. The same reduction in asset losses results in different welfare gains depending on who benefits. And some policies, such as adaptive social protection, do not reduce asset losses, but still reduce welfare losses. Asset and welfare losses can even move in opposite directions: increasing by one percentage point the share of income of the bottom 20 percent in the 90 countries would increase asset losses by 0.6 percent, since more wealth would be at risk. But it would also reduce the impact of income losses on wellbeing, and ultimately reduce welfare losses by 3.4 percent.

Is a five-day workweek followed by a two-day weekend a socially optimal schedule? This paper presents a model in which labor productivity and the marginal utility of leisure evolve endogenously over the workweek. Labor productivity is shaped by two forces: restfulness, which decreases over the workweek, and memory, which improves over the workweek. The structural parameters of the model are disciplined using daily variation in electricity usage per worker. The results suggest that increases in the ratio of vacation to workdays lead to output losses. A calibration of the model suggests that a 2-3 day workweek followed by a 1 day weekend can increase welfare.

This paper develops a novel methodology to measure the quantity of jobs and value of wages embodied in exports for a large number of countries and sectors for intermittent years between 1995 and 2011. The resulting Labor Content of Exports database allows the examination of the direct contribution of labor to exports as well as the indirect contribution via other sectors of the economy for skilled and unskilled labor. The analysis of the new data sets documents several new findings. First, the global share of labor value added in exports has been declining globally since 1995, but it has increased in low-income countries. Second, in line with the standard Hecksher-Ohlin trade model, the composition of labor directly contained in exports is skewed toward skilled labor in high-income countries relative to developing countries. However, that is not the case for the indirect labor content of exports. Third, manufacturing exports are a key source of labor demand in other sectors, especially in middle- and low-income countries. And the majority of the indirect demand for labor spurred by exports is in services sectors, whose workers are the largest beneficiaries of exporting activities globally. Fourth, differences in the labor value added in exports share across developing countries appears to be driven more by differences in the composition of exports rather than in sector labor intensities. Finally, average wages typically increase rapidly enough with the process of economic development to more than compensate the loss in jobs per unit of exports. The paper also includes the necessary information to build the Labor Content of Exports database from the original raw data, including stata do-files and matlab files, as well as descriptions of the variables in the data set.

This paper quantifies the contributions to poverty reduction observed in Sri Lanka between 2002 and 2012/13. The methods adopted for the analysis generate entire counterfactual distributions to account for the contributions of demographics, labor, and non-labor incomes in explaining poverty reduction. The findings show that the most important contributor to poverty reduction was growth in labor income, stemming from an increase in the returns to salaried nonfarm workers and higher returns to self-employed farm workers. Although some of this increase in earnings may point to improvements in productivity, defined as higher units of output per worker, some of it may simply reflect increases in food and commodity prices, which have increased the marginal revenue product of labor. To the extent that there have been no increases in the volumes being produced, the observed changes in poverty are vulnerable to reversals if commodity prices were to decline significantly. Finally, although private transfers (domestic and foreign) helped to reduce poverty over the period, public transfers were not as effective. In particular, the reduction in the real value of transfers of the Samurdhi program during 2002 to 2012/13 slowed down poverty reduction.

As part of a national experiment in 2008, Chengdu prefecture implemented ambitious property rights reforms, including complete registration of all land together with measures to ease transferability and eliminate migration restrictions. A triple difference approach using the Statistics Bureau’s regular household panel suggests that the reforms increased consumption and income, especially for less wealthy and less educated households, with estimated benefits well above the cost of implementation. Local labor supply increased, with the young shifting toward agriculture and the old toward off-farm employment. Agricultural yields, intensity of input use, and diversity of output also increased. Improving property rights in peri-urban China appears to have increased investment and diversification.

The welfare impact of a disaster does not depend only on the physical characteristics of the event or its direct impacts in terms of lost lives and assets. Depending on the ability of the economy to cope, recover, and reconstruct, the reconstruction will be more or less difficult, and the welfare effects smaller or larger. This ability, which can be referred to as the macroeconomic resilience of the economy to natural disasters, is an important parameter to estimate the overall vulnerability of a population. Here, resilience is decomposed into two components: instantaneous resilience, which is the ability to limit the magnitude of the immediate loss of income for a given amount of capital losses, and dynamic resilience, which is the ability to reconstruct and recover quickly. The paper proposes a rule of thumb to estimate macroeconomic resilience, based on the interest rate (a higher interest rate decreases resilience and increases welfare losses), the reconstruction duration (a longer reconstruction duration increases welfare losses), and a “ripple-effect” factor that increases or decreases immediate losses (negative if enough idle resources are available to cope; positive if cross-sector and supply-chain issues impair the production of non-affected capital). An optimal risk management strategy is very likely to include measures to reduce direct impacts (disaster risk reduction actions) and measures to reduce indirect impacts (resilience building actions).

While scholars agree on the importance of land rental markets for structural transformation in rural areas, evidence on the extent and nature of their operation, including potential obstacles to their improved functioning, remains limited. This study uses household-level data from six countries to start filling this gap and derive substantive as well as methodological lessons. The paper finds that rental markets transfer land to land-poor, labor-rich, and more productive producers throughout. But vast cross-country variation in transfers and the fact that female managers could possibly improve their income by leasing out land point towards barriers to participation that policy might address. Methodological and substantive conclusions are derived.

Drawing on a new set of nationally representative, internationally comparable household surveys, this paper provides an overview of key features of structural transformation—labor allocation and labor productivity—in four African economies. New, micro-based measures of sector labor allocation and cross-sector productivity differentials describe the incentives households face when allocating their labor. These measures are similar to national accounts-based measures that are typically used to characterize structural changes in African economies. However, because agricultural workers supply far fewer hours of labor per year than do workers in other sectors, productivity gaps disappear almost entirely when expressed on a per-hour basis. What look like large productivity gaps in national accounts data could really be employment gaps, calling into question the prospective gains that laborers can achieve through structural transformation. These employment gaps, along with the strong linkages observed between rural non-farm activities and primary agricultural production, highlight agricultures continued relevance to structural change in Sub-Saharan Africa.

The Government of Kenya recognizes that the performance of the furniture sector is crucial both to employment and growth in the country. The Ministry of Industrialization and Enterprise Development (MOIED) therefore requested an analysis of both the furniture and timber sectors, in order to understand their current state of development, their main constraints, and the interventions necessary to accelerate their growth. The objective of this report is to provide a comprehensive value-chain analysis of the Kenyan furniture industry, including the timber sub-sector, in order to assess policy options available to the MOIED and recommend critical interventions to stimulate the industry’s development. By situating Kenya’s furniture industry within the global and regional context, this paper also aims to identify ways in which to boost Kenya’s competiveness in the East African markets and beyond. The analysis in this report is largely focused on the wooden furniture sector (versus plastics, composites, and other furniture). The bulk of Kenya’s furniture industry is focused on wood, and Kenya has a competitive advantage in wood relative to South Africa, Asian countries, and Europe, which have very competitive value chains in furniture made from other materials.

The LACEX dataset has been recently assembled to compute the (direct and indirect) value of the compensation of employees linked to exports for each sector/country/year. The data has been computed on the basis of a panel of global input-output data spanning intermittent years from 1995 to 2007 from the Global Trade Analysis Project (GTAP). This represents a form of social accounting data - a variation on the social accounting matrix (SAM) where incomes are shown in the rows of the SAM while expenditures are shown in the columns. The structure of the data provides a comprehensive and consistent record of national income accounting relationships between different sectors and regions, including intermediate and final demand linkages. This structure of the dataset allows one to obtain the value added content of final output and exports, including its compensation of employees’ component. That includes both the direct and indirect compensation, based on the backward linkages of each sector with the rest of the economy. In order to obtain these labor value added measures, two intermediate multiplier matrixes need to be calculated. The first is the Leontief inverse matrix, which measures the inputs contained in a unit of final output. This matrix contains both direct and indirect inputs. Next, one needs to calculate a matrix which has the compensation of employees’ shares of total output. Using these two matrixes as multipliers one can obtain the compensation of employees’ shares of exports and final outputs. These shares are also split between skilled and unskilled workers.