Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This paper uses an analytically tractable intertemporal framework for analyzing the dynamic pricing of a utility with an underdeveloped network (a typical case in most developing countries) facing a competitive fringe, short-run network adjustment costs, theft of service, and the threat of a retaliatory regulatory review that is increasing with the price it charges. This simple dynamic optimization model yields a number of powerful policy insights and conclusions. Under a variety of plausible assumptions (in the context of developing countries) the utility will find its long-run profits enhanced if it exercises restraint in the early stages of network development by holding price below the limit defined by the unit costs of the fringe. The utility's optimal price gradually converges toward the limit price as its network expands. Moreover, when the utility is threatened with retaliatory regulatory intervention, it will generally have incentives to restrain its pricing behavior. These findings have important implications for the design of post-privatization regulatory governance in developing countries.

Choice --- Consumers --- Costs --- Debt Markets --- Demand --- Discount Rate --- Diseconomies of Scale --- E-Business --- Economic Efficiency --- Economic Theory and Research --- Emerging Markets --- Finance and Financial Sector Development --- Financial Literacy --- Incentives --- Investment --- Low Tariffs --- Macroeconomics and Economic Growth --- Marginal Costs --- Markets and Market Access --- Monopoly --- Optimization --- Prices --- Pricing --- Private Sector Development --- Profit Maximization --- Profits --- Urban Water Supply and Sanitation --- Utility --- Variables --- Water Supply and Sanitation --- Welfare

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This paper uses the night lights (satellite imagery from outer space) approach to estimate growth in and levels of subnational 2013 gross domestic product for 47 counties in Kenya and 30 districts in Rwanda. Estimating subnational gross domestic product is consequential for three reasons. First, there is strong policy interest in how growth can occur in different parts of countries, so that communities can share in national prosperity and not get left behind. Second, subnational entities want to understand how they stack up against their neighbors and competitors, and how much they contribute to national gross domestic product. Third, such information could help private investors to assess where to undertake investments. Using night lights has the advantage of seeing a new and more accurate estimation of informal activity, and being independent of official data. However, the approach may underestimate economic activity in sectors that are largely unlit notably agriculture. For Kenya, the results of the analysis affirm that Nairobi County is the largest contributor to national gross domestic product. However, at 13 percent, this contribution is lower than commonly thought. For Rwanda, the three districts of Kigali account for 40 percent of national gross domestic product, underscoring the lower scale of economic activity in the rest of the country. To get a composite picture of subnational economic activity, especially in the context of rapidly improving official statistics in Kenya and Rwanda, it is important to estimate subnational gross domestic product using standard approaches (production, expenditure, income).

Agricultural output --- Agricultural performance --- Agricultural sector --- Agriculture --- Annual growth --- Annual growth rate --- Cities --- City --- Coefficients --- Consumption --- Criteria --- Development indicators --- Development policy --- Diseconomies of scale --- Distribution of income --- District --- District administrations --- District level --- District-level --- Economic activity --- Economic decline --- Economic downturns --- Economic growth --- Economic theory & research --- Economics --- Elasticity --- Empirical model --- Estimation method --- Financial crisis --- Fiscal management --- Fixed effects --- GDP --- GDP per capita --- Gross domestic product --- Growth --- Growth rate --- Growth rates --- Household surveys --- Incentives --- Incidence of poverty --- Indicators --- Informal economy --- Inputs --- Long-term growth --- Macroeconomics --- Macroeconomics and economic growth --- National poverty line --- Policy research --- Poverty --- Poverty impact evaluation --- Poverty levels --- Poverty line --- Poverty reduction --- Pro-poor growth --- Provinces --- Real GDP --- Resource allocation --- Revenue --- Revenue allocation --- Revenue sharing --- Revenue sharing formula --- Revenue-raising capacity --- Subnational entities --- Subnational governments --- Subnational unit --- Surveys --- Tax --- Underestimates --- Urban areas --- Wealth