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Global Trade Data
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World Economics, December 2019
There are serious problems with official trade statistics since according to the IMF in 2016 the world imported US$339 billion more than it exported. The Ricardian concept of comparative advantage in final goods is no longer fully relevant to explain trade between countries and the solution is to operate a paradigm shift in the packaging and interpretation of trade data. The accuracy and reliability of data is affected by a number of key biases separate from data quality issues and misreporting. The main problems are trade data asymmetries; the Rotterdam Effect and the impact of global value chains. Until this happens international trade statistics will be used as evidence of global trade imbalances and form the basis of potentially misguided policies aimed at their correction.
Global Population Data Quality Ratings
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World Economics, April 2020
There is no summary available for this paper.
Why Price Data Are Mostly Wrong
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World Economics, April 2020
Is US GDP 51% bigger than China’s? Or is China 2.4% bigger than the US? It’s all down to how you measure prices. Here’s why…
GDP per Capita Data Quality Ratings
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World Economics, April 2020
There is no summary available for this paper.
The Alarming Problems Caused By Misleading Trade Data
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World Economics, March 2020
The fact that world exports do not match world imports indicates that there are serious problems with official trade statistics. Far too few economists and politicians will try to understand the murky reality behind these increasingly unreliable data.
Data Quality Rating: China
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World Economics, September 2019
The quality of GDP data in China is improving, and up to date in many respects. But is still some way from good quality. Use with caution!
How Accurate are Global Trade-Finance Data?
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Brian Sturgess, World Economics, June 2019
Over 80% of international trade is financed by some form of credit, but the size of the trade finance market has received little attention by economists. It has been estimated that there is currently a world trade finance gap of around US$1.5 trillion acting as a drag on international trade and GDP growth. Survey-based estimates of traditional trade finance provided by banks at US$4.6 trillion in 2017 are highly inconsistent and are based on flawed data and opaque methodologies. The problem of collecting reliable data needed to promote trade growth and to monitor financial stability is being exacerbated as the trade finance sector is undergoing rapid structural change.
Saudi Arabian Labour Market Data Outlines the Challenges of Reform
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Brian Sturgess, World Economics, March 2019
Saudi Arabia’s Council of Ministers approved an ambitious National Transformation Programme (NTP) in June 2016 with the aim of carrying out a complete restructuring of the economy. The implementation of Vision 2030 has major implications for the structure of Saudi Arabia’s labour market with the creation of 1.2 million non-oil private sector jobs, most of which are expected to be taken up by citizens. Official data shows the labour market has a number of distinctive features which will challenge the implementation of Vision 2030: an overreliance on expatriate labour; a preference by nationals for public sector jobs; a gender imbalance; persisting structural unemployment and problems in balancing labour supply and demand. The government is attempting to change the operation and structure of the labour market by a set of policies involving quotas, subsidies, taxes, penalties and the provision of information services, but for a number of reasons change is unlikely to proceed smoothly in the next few years.
Inequality: Concepts, Data, Perspectives and Solutions
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Michael Chibba & John M. Luiz, World Economics, March 2019
A comprehensive treatise on inequality from economic, social, business and metrics/data perspectives is lacking in the literature and this treatise fills that void. We posit that: (a) neoclassical economics has failed to address inequality within nations; (b) the social theories on inequality are of ancillary importance; (c) businesses have contributed to inequality in several ways but have also made a positive contribution towards a fairer, more equitable society; (d) data on inequality is not up to date. Taxation and social programs offer an inadequate approach to tackling inequality without a proper framework and supporting approaches. In addition, complementarity between neoclassical economics and behavioural economics would be a positive factor in addressing inequality and should be pursued. Issues of inequality metrics and data reliability have moved to the forefront of discussions as the data currently available is the basis of much dissent. Robust metrics and reliable and up to date inequality data (as well as related statistics) are indispensable for designing, implementing, monitoring, and evaluating inequality interventions and policies.
Data, Deceit, and the Defence of Truth
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Stuart P.M. Mackintosh, World Economics, September 2018
Attacks on experts and professionals using available facts, are rising in the USA, with troubling implications for economics, for the collection of statistical data, and for the future integrity of the policymaking process. The Trump Administration is undermining fact-based decision making in a number of discreet interventions: Citizenship questions for the upcoming decennial census and in attacks on the work of an economist in the US Congressional Budget Office on healthcare costs. In Argentina from 2002 until 2015 the Kirchner government twisted the output of the official statistical agency to their own aims, publishing bogus data on inflation, GDP, and poverty. In Greece the efforts of Andreas Georgiou from 2010 to 2015 to correct the biased output on GDP and government expenditure data at the Greek Statistical Agency led a judicial persecution all the way to the Greek Supreme Court.
The Seemingly Underappreciated Role of Panel Data in Measuring Poverty and Economic Transformation
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Hai-Anh H. Dang & Calogero (Gero) Carletto, World Economics, September 2018
Panel survey data play a crucial role in producing estimates on welfare dynamics as well as insights into transformation processes in developing economies. Panel survey data are indispensable for effective policy advice for poverty reduction and growth. Fielding and maintaining a good-quality panel survey requires investment in financial and technical resources as well as careful planning, especially in developing countries. Statistical techniques can also be employed to produce estimates on poverty dynamics as an alternative methodology, but a new hybrid approach can combine the advantages of both methods.
Error in Demographic and Other Quantitative Data and Analyses
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Thomas Burch, World Economics, June 2018
Statistical data consumed, analysed and produced contain errors from more sources than is often recognised and the commercialisation of survey and other statistical research and ‘inventions’ such as ‘big data’ has led to naïve and faulty analysis and propaganda. Oskar Morgenstern has noted that, in contrast to physics, there is no estimate of statistical error within economics and the various sources of error that come into play in the social sciences suggest that the error in economic observations is substantial. It is important to recognise the phenomenon of the propagation of errors; errors in our results may be disproportionate to errors in our input data. Despite documented problems social scientists cannot give up on quantitative data since many of the most important questions in social science are matters of more or less, not either/or.
Debt, Economic Growth and Data Adequacy
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Vighneswara Swamy, World Economics, June 2018
The effects of government debt on economic growth has become of immense importance in the backdrop of the Eurozone sovereign debt crisis and Reinhart & Rogoff’s related research. This study is based on a sizeable dataset which extends the horizon of analysis to country groupings and makes it inclusive of economic, political, and regional diversities. The study overcomes issues related to data adequacy, coverage of countries, heterogeneity, endogeneity, and non-linear relationships by conducting a battery of robustness tests. An increase in the debt-to-GDP ratio is found to be associated with a reduction in average growth, but the relationship is nonlinear.
Commercial Real Estate Data - New Demands, Old Challenges
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David Rees, World Economics, March 2018
The global financial crisis, followed by a global portfolio shift towards commercial real estate, has reinforced the demand for timely, consistent and transparent valuation metrics and transactions data. Current initiatives at global, country and market level are addressing shortcomings in this area; nevertheless commercial real estate markets pose unique data collection and presentation challenges. While users of these data should be aware of the difficulties and qualifications inherent in the collection and compilation process, enforcing uniformity of processes and definitions across markets and sub-sectors may come at a cost. Propositions that more data are always better than less and that market transparency is always better than opacity are fruitful topics for debate in the context of commercial real estate markets.
Using Price-Adjusted Income Data to Measure Regional Income Inequality Across the UK
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Julian Gough, World Economics, March 2018
Data for gross disposable household income for each region of the UK are published annually by the Office for National Statistics. The latest provisional data available are for the year 2015. The annual data for household income are in nominal terms only—i.e. they do not allow for differences in prices between regions of the UK, which distorts the results. A reliable deflator to correct the nominal data for differences in inter-regional price levels was derived from the regular survey of prices for calculating the Retail Prices Index, augmented by a special survey of prices of goods and services. When allowing for price level variations between nominal and real household income in different regions the greatest impact is on London. In real terms, household incomes in London are 6% lower than in nominal terms, amounting to a reduction of about £12.4 billion.
Analysis of Revisions in Indian GDP Data
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Amey Sapre & Rajeswari Sengupta, World Economics, December 2017
This paper studies constant price growth estimates of India’s annual GDP data in order to understand the revision policy adopted by the Central Statistics Office. The use of high-frequency indicators to prepare initial estimates overstates the growth of the economy, although at the aggregate level the difference between initial estimates and final revisions is low. At the sectoral level the extent of revision for almost all sectors is large and the magnitude and direction of the revision is unpredictable. The Central Statistical Office must address issues in data quality and revisions by (i) adopting a comprehensive revision policy, (ii) supplying information and data on high frequency indicators and (iii) adopting revision metrics to assess the quality of estimates.
Trade Data: Use with Care
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Brian Sturgess, World Economics, December 2017
Politicians focus on trade deficits and surpluses between countries and threaten trade wars and retaliatory actions, but the conventional international trade statistics used by many commentators are inaccurate. World exports and imports do not balance, but asymmetries are also found in the balance of trade statistics between countries and regions and these discrepancies can be very large in emerging markets. The ‘Rotterdam effect’ distorts the measurement of trade flows and balances where goods are recorded as imports into one country, which subsequently re-exports them to third countries without taking note of the country of origin. The Apple ‘Made in China’ question, or the existence of global value chains where much trade is in intermediate inputs, indicates that conventional trade statistics involve double-counting and misallocated trade balances.
Making Data Measurement Errors Transparent: The Case of the IMF
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Peter A.G. van Bergeijk, World Economics, September 2017
In 1950 Morgenstern pointed out that absolute precision and certainty are impossible in economic observations, but estimates are often hampered by a substantial degree of measurement error. Unlike the natural sciences, economists in general do not report measurement errors for the key concepts such as prices, value or production that it seeks to define, measure and explain. For most macroeconomic concepts two approaches are available: the Implicit Minimal Measurement Error and the Maximum Ratio. Studying different vintages of the IMF World Economic Outlook data base it was found that the estimates on average have an implicit minimal measurement error of 4.3% and maximum ratio of 17.9%. An agenda is proposed for removing disincentives (creating incentives) for stakeholders (academics, data collectors and producers) since reporting measurement error will result in better research, better policy and ultimately better data.
The Data Quality Index
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World Economics, June 2017
GDP data is important used to apportion funds from international organisations, to influence rating agency decisions and much more, but official data is totally inadequate for the demands made of it. The notion of GDP data is flawed conceptually, but there are also severe methodological issues that need to be addressed prior to making international comparisons and assessing data reliability. World Economics has created an interactive Data Quality Index for users of economic data which considers five readily measurable factors that influence data reliability across countries. The Data Quality Index ranks 154 countries based on an equal weighting of the five factors, but users can adjust the importance of each to their data needs.
Double Deflation Casts Doubt on Existing GDP Data
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Brian Sturgess, World Economics, June 2017
Increasingly, national income statisticians, the specialists involved in producing real national income figures, and the users of those figures are living in a parallel universe. Most countries use an outdated and inaccurate method to estimate real Gross Domestic Product (GDP) by using what is termed single deflation. Best practice suggests using double deflation: one price index to deflate the prices of goods produced and another to deflate the value of intermediate goods used up in production. A recent study comparing single deflation calculations with double deflation official growth estimates for eight countries showed that, for some years, single deflation figures deviated up- or downwards from the official estimates by as much as 3–4 percentage points.

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