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Estimating Loss-in-Output as a Cost of a Financial Crisis
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Vighneswara Swamy, World Economics, June 2019
The global financial crisis caused a huge loss of economic output, depletion of financial wealth, extended unemployment, psychological consequences and other significant costs. A quantitative exploration of modelling loss-in-output as a cost of financial crisis using macroeconomic indicators is useful in understanding the impact of a crisis. The conservative estimates for India suggest that, over a period of ten years, a financial crisis can cause a cumulative loss-in-output ranging from 48% of GDP to 59% of GDP after discounting at 0.025 and 0.07 respectively. Intermediate values are also explored. Estimating loss-in-output in terms of GDP simplifies estimation of the impact of financial crises. Policymakers and regulators must be more prudent and alert in sensing the early indicators of a financial crisis and act swiftly in containing its perils.
The Financial Crisis and Gender: Assessing Changes in Workforce Participation for Rural India
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Siddhartha K. Rastogi & Pradyun Rame Mehrotra, World Economics, March 2018
Labour market data in India shows female participation declining as GDP has increased, a phenomenon found in other East Asian economies over past two decades. This contradicts empirical observations, which argue over the feminization of the work force due to participation in global export markets, primarily driven by wage efficiency of female labour. The impact of the global financial crisis on female participation rates in rural India in 2009-10 is studied with a cross-state analysis to test theories about female unemployment in a downturn. One of the major findings is that as the formal wage difference between men and women decreases, the female participation gap increases, but more data is needed to identify critical causal factors.
Are Estimates of the Economic Contribution of Financial Services Reliable
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Brian Sturgess, World Economics, March 2017
The methods used to estimate the contribution of financial services to national income are seriously flawed. Banking sector output in the UK was estimated to have increased in 2008 while the financial services sector was collapsing. The relative contribution of service activities in GDP is not easy to measure, but there are many problems in measuring financial services in general and the output of banks in particular. National income accounting standards, used to estimate the output of financial intermediation companies such as banks, rely on flawed indirect measurements based on interest rate spreads. Furthermore, many services are provided at no charge so price indexes cannot be meaningfully created. The main method used, Financial Intermediation Services Indirectly Measured (FISIM), is arbitrary and fails to measure the quality of banking assets and risk. Over the period 2003–7, one study found that aggregate risk-adjusted output would have been only 60% of officially estimated output across the Euro area.
Measuring Financial Inclusion using Multidimensional Data
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Mandira Sarma, World Economics, March 2016
The author notes that the lack of a financially inclusive system is a major concern not only for developing and low-income economies, but for many developed and high-income countries. At the global level, a network of financial regulators from developing and emerging economies, called the Alliance for Financial Inclusion (AFI), was formed in 2008 to provide a platform for peer-to-peer learning from the experiences of country specific policies of financial inclusion. The paper notes that there has been an intensive debate about how financial inclusion should be measured. In consequence, it recommends using the Index of Financial Inclusion (IFI), developed by the author. The IFI is multidimensional, it satisfies many important mathematical properties and can be used to compare levels of financial inclusion across economies and over time. IFI values computed for 110 countries for 2014 show various levels of financial inclusion: Chad ranked lowest with an IFI value of 0.021 while Switzerland had a value of 0.939. Measuring the IFI over 2004 – 2014 indicates a general improvement in the level of financial inclusion across countries, but the availability of data is the biggest constraint on its usefulness.
GDP figures: How the Financial Times gets it wrong
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David Henderson, World Economics,
Dollar market exchange rates are erroneously used by many publications to make cross-country comparisons of GDP. Exchange rates underestimate the relative size of developing economies and provide misleading estimates of important economic ratios such as energy intensity figures. The United Nations System of National Accounts recommend the use of Purchasing Power Parity converters which account for cross-country differences in price levels.

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