The primary motivation for predicting data in economics, health sciences, and other disciplines has been to deal with various forms of missing data problems. However, one could also make a case for adopting prediction methods to obtain more cost-efficient estimates of welfare indicators when it is expensive to observe the outcome of interest (in comparison with its predictors). For example, consider the estimation of poverty and malnutrition rates. The conventional estimators in this case require household- and individual-level data on expenditures and health outcomes. Collecting this data is generally costly. It is not uncommon that in developing countries, where poverty and poor health outcomes are most pressing, statistical agencies do not have the budget that is needed to collect these data frequently. As a result, official estimates of poverty and malnutrition are often outdated: For example, across the 26 low-income countries in Sub-Saharan Africa over the period between 1993 and 2012, the national poverty rate and prevalence of stunting for children under five are on average reported only once every five years and once every ten years in the World Development Indicators.
This question is particularly relevant in the context of traditional public agricultural extension services. Expensive and burdened by high rates of under-staffing and low levels of accountability, privatization of extension services may be a way to improve cost-effectiveness. However, private services may lack incentives to tailor their services to the poorest, making them an unsatisfactory substitute for a public system of extension. This issue is particularly salient in sub-Saharan Africa, where markets for agricultural services are typically lean.
This is the third of three blog posts on recent trends in national inequality.
In earlier blogposts on recent trends in inequality, we had referred to measurement issues that make this exercise challenging. In this blogpost we discuss two such issues: the underlying welfare measure (income or consumption) used to quantify the extent of inequality within a country, and the fact that estimates of inequality based on data from household surveys are likely to underreport incomes of the richest households. There are a number of other measurement challenges, such as those related to survey comparability, which are discussed in Poverty and Shared Prosperity 2016 – for a focus on Africa, also see Poverty in a Rising Africa, published earlier in 2016.
In 2014, Australian startup founder Evan Thornley gave a talk at a technology startup conference about why he likes to hire women. So far, so good. However, things quickly deteriorated when he explained that part of the reason was that women were “still often relatively cheap compared to what we would’ve had to pay someone less good of a different gender”, illustrated by a slide that read “Women. Like men, only cheaper”.
While the ensuing media outcry quickly forced Thornley to backtrack on his comments, the reality his slide so eloquently put into words is not so easily revised. Even in Silicon Valley, considered one of the most forward-thinking industries in the world, women continue to be paid less than their male counterparts.
When the Plantagenet kings ruled England (1154-1485), their primary means of securing wealth, prestige, and power was through territorial conquest. Fighting endless wars in France and dispatching armies as far as Jerusalem, the crown often had to finance foreign adventures through taxation -- sometimes crushing taxation – of subjects. The illegitimacy of such taxation only intensified the recurrent threat of domestic revolt. And through their demands for more accountable and inclusive governance, the English nobility succeeded, albeit with much blood shed over a span of centuries, to establish institutions and public policies conducive to economic development.
Conventionally the governing law should not affect the cost of borrowing in international markets. If it did, borrowers would use the cheaper jurisdiction. Also, if somehow the spread differed at the time of the launch of the bond, trading in the secondary market should eliminate the difference. A recent paper shows otherwise: Sovereign bonds issued under the UK law had a persistent higher spread than those under the US law, but only since the global financial crisis in 2008.
Historically, U.S. law issuances formed the dominant part of the volume of dollar-denominated central government bond issuances, barring 2012 when U.K. law issuances briefly overtook U.S. law issuances (Figure 1). There were also divergences in characteristics of dollar-denominated central government bonds issued across the two jurisdictions. Average spread at launch for bonds issued under U.K. law became distinctly higher after the global financial crisis in 2008 (Figure 2). On average, bonds issued under U.K. law also had weaker ratings and shorter tenors post-crisis.
The previous blog post in this series described the trend in the global and regional averages of national inequality for the period 1988-2013. Now we dig deeper into the trends in inequality at the country level. We describe changes in national inequality during two periods – around 1993 to 2008 and around 2008 to 2013. The long-run spells include all countries for which we have data on inequality around 1993 and 2008, and that data is computed using the same welfare measure (income or consumption). The short-run spells include countries for which we have inequality data around 2008 to 2013; this list is based on the World Bank’s Global Database of Shared Prosperity.
The Organization of the Petroleum Exporting Countries (OPEC) unsettled oil markets in September when it announced it would resume placing limits on oil production among its members, effectively reversing two years of unrestrained production.
But how much control can OPEC really exert over prices? History suggests that formal agreements to influence the price of a particular commodity eventually fall apart. OPEC’s own history also shows that the short term benefits of managing supplies become long term liabilities. In addition, the oil producing landscape has changed dramatically in recent years with the advent of nonconventional producers, notably the U.S. shale oil industry. These factors will test the oil exporting organization’s power to influence markets.
Prices for most commodities, including oil, are forecast to rise in 2017 as a long period of declining prices appears to be bottoming out, according to the October Commodities Markets Outlook.
Oil prices are forecast to rise to $55 per barrel next year from $43 per barrel in 2016 as markets readjust after an era of abundant supply that outpaced demand. Energy prices, which also include coal and natural gas, are forecast to jump 24 percent in the coming year. The decision in September of the Organization of the Petroleum Exporting Countries (OPEC) to resume limiting oil production is another important factor behind the higher price forecast.
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This is the first of three blog posts on recent trends in national inequality.
Inequality has featured prominently in the public debate in recent times. Media outlets highlight the apparent surge in the incomes of the richest, many books have been written on this issue, and numerous academic studies have attempted to assess the nature and magnitude of inequality over time. Most studies of inequality focus on the extent of inequality within a country; this makes sense since most policies operate at this level, too. Despite the attention this issue has received, it has been constrained by the quality of data on inequality. Household surveys collected by national authorities around the world are the most readily available source of data on inequality. However, compiling and harmonizing household surveys from different countries is extremely difficult as they are not always collected consistently or frequently enough. It is also well-known that household surveys often fail to capture the top tail of the distribution, as we will discuss in more detail in a future blog.