5 following the seminal work of Krueger, Schiff, and Valdés (1988; 1991), which covered between 15 and 25 years prior to 1985 for just 17 developing countries.<sup>4</sup> Fortunately, a new database of agricultural distortions has been developed recently by the World Bank (Anderson and Valenzuela 2008, updated and extended by Anderson and Nelgen 2012b). This new data complements and extends the OECD’s PSE/CSEs and the Krueger, Schiff, and Valdés studies. It builds on those earlier databases by providing similar estimates for other significant (including many low-income) developing economies, by estimating new and more comprehensive policy indicators, and by providing measures of price distortions also for non-agricultural tradables.

The new World Bank database includes estimates for 82 countries, which together account for between 90 and 96 percent of the world’s population, farmers, extreme poor living on less than $1.25 per day, agricultural GDP, and total GDP. The sample countries also account for more than 85 percent of agricultural production and employment in each of Africa, Asia, Latin America, and the transition-economies region of Europe and Central Asia, as well as for all of agricultural production and farm employment in OECD countries. In the data set, the spectrum of per-capita incomes ranges from some of the poorest countries (Zimbabwe and Ethiopia) to some of the richest (Norway). Not all countries had annual data for the entire 1955–2010 period, but the average number of years covered is 45 per country. (The full list of developing countries by region, plus lists of the transition economies and high-income countries in the data set, is provided in the Appendix Table.) Nominal Rates of Assistance (NRAs) and Consumer Tax Equivalents (CTEs) are computed for 75 different farm products, with an average of almost eleven per country. This product coverage represents about 70 percent of the gross value of agricultural production in each of the focus countries and just under two-thirds of global agricultural production, valued at undistorted prices over the period covered. Of the world’s 30 most valuable agricultural products, the NRAs cover 77 percent of global output (ranging from two-thirds for livestock to three-quarters for oilseeds and tropical crops and five-sixths for grains and tubers). These products represent 85 percent of global agricultural exports.

Such comprehensive coverage of countries, products, and years offers the prospect of generating a reliable picture of long-term trends in policy indicators for individual countries and commodities, as well as for country-groups, regions, and the world as a whole. This data set reveals distinct patterns of price distortions across countries and over time, only some of which has the literature to date identified and explained. These patterns are summarized here under four headings: sectoral distortion variation across countries; intrasectoral variation across products; year-to-year variations in rates of distortion; and policy-instrument choices. Before presenting estimates for each of these pattern categories, we first present the pricedistortion measures used.

# **_2.1. Measures of Price Distortions_**

Historically, agricultural and non-agricultural trade measures (border taxes and protectionist Non-Tariff Barriers, or NTBs), together with multiple exchange rates, have distorted product prices more commonly than have trade subsidies, direct domestic producer or consumer subsidies, or domestic taxes or quotas that alter product or input prices. However, in highincome countries since the 1970s, export subsidies have grown in importance; and, since the

> 4 An exception is a set of estimates of nominal rates of protection for key farm products in China, India, Indonesia, and Vietnam since 1985 by Orden et al. (2007). The OECD (2009) also has released PSEs for Brazil, China, and South Africa, as well as several Eastern European countries, which have since been updated to 2010 (OECD 2011).