Responding to Recession: Evidence from Thailand
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World GDP fell by 0.6% in 2009. Buffeted by the shocks created by the great recession, the Thai economy contracted by 2.3% in that year. In this paper we ask how large the shocks to the Thai economy in 2008-09 were, how Thai households were affected by the shocks, and the extent to which the government’s response cushioned those effects for different groups of households.
Following the three-layer approach recommended by Bourguignon and Pereira da Silva (2003), we first quantify the magnitude of the reductions in exports (broken down by group) and tourism, by comparing the actual values with a plausible counterfactual. We estimate that from October 2008 through September 2009, tourist arrivals were 12% below trend, and the dollar value of exports fell by 16%.
In the second layer we use a SAM multiplier analysis (following Round 2003) to measure the direct, indirect, and induced effects of the exogenous shocks to tourism and exports, using an updated 81-sector Social Accounting Matrix that has 61 “industrial” sectors. This allows us to simulate the effects of the shocks on the income in each sector.
For the third layer we map the sectoral changes in incomes to household incomes, using data from the Socio-Economic Surveys, which sample about 3,500 households every month. This allows us to measure the effects of the shocks on the distribution of income, as well as along other dimensions, including region and gender.
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Liberian dollar
Fell
Social accounting matrix
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Abstract The authors examine the changes in the level and composition of consumption expenditures and their associations with household per capita incomes across the four different economic shocks that Russia has experienced since 1994. Data were collected from a nationally representative annual panel survey of households between 1994 and 2014, supplemented by the Federal State Statistics Service source. Four hypotheses on the relationship between per capita income and consumption, the composition of cutbacks, a levelling of expenditures among income groups, and the stability of the pattern of consumer response to economic shocks are proposed. The data demonstrate that consumption expenditures on food, non‐food, and services decreased together with per capita income during the four economic shocks. Only a few examples of significant smoothing effects were found. All income groups recomposed their expenditures to maintain consumption of necessities. The high‐income group reduced a higher proportion of expenditures on food and services, implying that economic shocks produce a temporary levelling effect on the living standards of different income groups. A relatively stable pattern of consumer responses to economic shocks was revealed, despite these shocks’ divergence; this pattern implies a temporary economization and simplification of expenditures with a fast return to pre‐crisis spending once the crisis is over.
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Levelling
Per capita income
Consumption smoothing
Consumer spending
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Global economic growth projections for 2020 have been revised downward, reflecting a dramatic worldwide economic downturn that has been driven by lockdowns associated with the COVID-19 pandemic that sharply restricted workforce mobility and trade flows.Jordan is no exception to this pattern, as the International Monetary Fund (IMF) recently revised downwards it outlook on expected levels of growth for the Jordanian economy through 2020 (IMF 2020a).Economic growth in Jordan potentially will come to a halt this year.This comes as a result of the COVID-19 pandemic outbreak.Government imposed an economic lockdown which restricted non-essential economic activities and people's movement in order to contain the virus.A SAM multiplier model was used to estimate the economic impact of the lockdown and to explore potential recovery pathways for the Jordanian economy.Some of the key findings from this modeling exercise are:• National GDP is estimated to have fallen by 23 percent during the lockdown period.The services sector was hardest hit, seeing an estimated drop in output of almost 30 percent.• Food systems in Jordan are estimated to have experienced a reduction in output by almost 40 percent.• Employment losses during the lockdown were estimated at over 20 percent, mainly driven by job losses in services, followed by agriculture.• Household income fell on average by around one-fifth due to the lockdown, mainly driven by contraction in service sector activities, by slowdown in manufacturing activity, and by lower remittances from abroad.• GDP growth rates for Jordan's economy will continue to be negative through 2020, ranging from -5.7 to -7.4 percent, depending on the speed of economic recovery.A slow pace of recovery is expected.This economic recovery offers opportunities for fostering sustainable economic transformation and structural change.Economic policies and incentives should be directed towards more economic diversification, greater resilience to withstand economic shocks, and job creation.
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On November 8, 2016, the Indian government abruptly demonetized 86% of its currency in circulation in an attempt to reduce black money, corruption, and counterfeiting. Yet, 99% of the currency was eventually returned to banks. In this paper, we empirically investigate the medium-term effects of the policy. We document that both poorer regions and poorer households experienced relative and absolute increases in economic outcomes over the year and a half that followed. Using monthly night-light data, we estimate that districts in the poorest quintiles experienced an increase in GDP per capita 11% greater than the richest. For the household analysis, using a longitudinal survey of expenditures and incomes, we also show that the poorest quintiles had relative increases in expenditures and incomes of 35% and 18% respectively in the following eighteen months.
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Consumption smoothing
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Abstract We study the short‐ and medium‐term impacts of the recent recession on the distribution of net household income in the UK. We document trends in the distribution of income during and immediately after the economy's 6.3 per cent contraction between 2008Q1 and 2009Q2. We then use a tax and benefit microsimulation model combined with macroeconomic and demographic forecasts to project the distribution of income up to 2015–16. As in other countries, immediate impacts of the recession on net household incomes are remarkably hard to detect, but the pain was merely delayed until 2010–11 and beyond. We find that the major difference between income groups is in the timing of the reductions in income, rather than in their magnitude. For those in the middle and upper parts of the distribution, dependent mainly on labour market income, falls in real income happened largely between 2009–10 and 2011–12. For those towards the bottom, dependent more on benefit incomes, falls in real income will happen largely as a result of the post‐recession fiscal tightening between 2010–11 and 2015–16. We explore the sensitivity of the results to different scenarios for employment and earnings: the central and qualitative conclusions prove robust.
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Net national income
Household income
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The 1992-93 recession in the western states of Germany has been attributed, in substantial measure, to the macroeconomic consequences of policies to finance unification. Studies of the costs of unification have not attempted to measure the burden of the recession. We estimate a dynamic, panel model of household incomes using data from the German Socio-Economic Panel (GSOEP) and use it to forecast what these incomes would have been in 1992-94 without a recession. Using a ratio of actual to forecast incomes, we compare the relative burden of the recession across households. Our findings suggest that western households below the median income bore the brunt of the combined impact of unification and the recession of 1992-93.
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The COVID-19 pandemic is expected to considerably affect the Ethiopian economy directly and indirectly due to global shocks and to the different restrictive preventative measures the country is taking. We analyze these economic effects using multisector economywide income multiplier models built on the two latest Social Accounting Matrices (SAMs) developed for Ethiopia. Three external sector channels are the focus of the analysis: commodity exports, strategic imports, and remittances. Results indicate that in the absence of any policy responses, the Ethiopian economy is expected to experience a loss of approximately 4.3 to 5.5 percent of its annual GDP due to exports, strategic imports, and remittances that are one-third lower relative to the no-COVID situation over a period of six-months. This translates into estimated reductions in labor income of between 4.2 and 5.2 percent. The SAM multiplier model estimates also imply that these negative shocks lead to household income losses that amount to between 3.9 and 6.4 percent. In particular, the urban poor will be the most affected as they lose real incomes in the range of 6.6 to 8.5 percent. These income losses are estimated to result in a 3.5 percentage point rise in the national poverty headcount.
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Estimates of income inequality and the dynamics of poverty are highly sensitive to measurement error and transitory shocks in micro-level data. The apparent high levels of economic mobility in Poland and Russia are driven largely by transitory shocks and noisy data. There is a real risk of an entrenched underclass emerging in these transition economies. Luttmer uses instrumental variable methods and the decomposition of income into transitory and persistent components to distinguish underlying income inequality and changes in poverty from the effects attributable to measurement error or transitory shocks. He applies this methodology to household-level panel data for Russia and Poland in the mid-1990s. Luttmer finds that: Accounting for noise in the data reduces inequality (as measured by the Gini coefficient) by 10-45 percent. Individuals in both countries face much economic insecurity. The median absolute annual change in income or spending is about 50 percent in Russia and about 20 percent in Poland. But roughly half of these fluctuations reflect measurement error or transitory shocks, so underlying levels of income and spending are much more stable than the data suggest. The apparent high levels of economic mobility are driven largely by transitory events and noisy data. After transitory shocks are accounted for, about 80 percent of the poor in both Russia and Poland remain in poverty for at least one year. So there is a real risk of an entrenched underclass emerging in these transition economies. This paper - a product of the Poverty Reduction and Economic Management Sector Unit, Europe and Central Asia Region - is part of a larger effort in the region to analyze poverty and inequality in Europe and Central Asia.
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The state tracks income changes between two groups of households, i.e., with incomes at or below and above social minimum during the period 2004-2008. The description of spatial variables accounting for differences across voivodships is followed by the description of differences in expenditures on major foods and food categories illustrating the gaps between two household groups over time. The income disparities have been growing during the period under consideration. Low-income households are relatively more dependent on staples and foods that are less desired from a nutritional standpoint. Results suggest the need for intensification of efforts to prevent the poor household segment falling into permanently poor households with possible detrimental effects for overall competitiveness of the national and regional economies. (original abstract)
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Slowdown
Falling (accident)
Household income
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In recent years, Korea had experienced two financial crises in 1997-1998 and 2007-2008 respectively and the IT revolution during the interval between the two financial crises. We have constructed Social Accounting Matrix (SAM) in 2000 and 2009 for Korea by combining Input-output tables used in WIOD project in Korea with data from 10-decile Urban Household Income Survey. We analyze gross income effect and income redistribution effect of financial crises and IT revolution by adopting a SAM framework following Pyatt and Round (2004) and Saari, Dietzenbacher and Los (2010). Both financial crises and IT revolution have generated larger income multiplier effect on Higher ITintensive Manufacturing sector but have affected negatively on income redistribution of lower income groups.
Social accounting matrix
Decile
Comprehensive income
Social accounting
Net national income
Household income
Net income
Adjusted gross income
Redistribution
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