Books on the topic 'Shock aggregati'

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1

Kim, Se-Jik. Aggregate shock, capital market opening, and optimal bailout. Seoul, Korea: Korea Institute for International Economic Policy, 2001.

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2

Braun, Helge. Aggregate shocks and labor market fluctuations. St. Louis, Mo.]: Federal Reserve Bank of St. Louis, 2006.

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3

Veldkamp, Laura. Aggregate shocks or aggregate information?: Costly information and business cycle comovement. Cambridge, Mass: National Bureau of Economic Research, 2006.

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4

Ball, Laurence M. Relative-price changes as aggregate supply shocks. Cambridge, MA: National Bureau of Economic Research, 1992.

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5

Ball, Laurence. Relative-price changes as aggregate supply shocks. Philadelphia: Federal Reserve Bank of Philadelphia, Economic Research Division, 1993.

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6

Ferreira, Francisco H. G. Aggregate economic shocks, child schooling and child health. [Washington, D.C: World Bank, 2008.

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7

Bordo, Michael D. Aggregate price shocks and financial instability: An historical analysis. Cambridge, MA: National Bureau of Economic Research, 2000.

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8

Doepke, Matthias. Inflation as a redistribution shock: Effects on aggregates and welfare. Cambridge, Mass: National Bureau of Economic Research, 2006.

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9

Doepke, Matthias. Inflation as a redistribution shock: Effects on aggregates and welfare. Cambridge, MA: National Bureau of Economic Research, 2006.

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10

Hutchison, Michael M. Aggregate demand, uncertainty and oil prices: The 1990 oil shock in comparative perspective. Basle: Bank for International Settlements, Monetary and Economic Department, 1991.

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11

Bordo, Michael D. Aggregate price shocks and financial stability: The United Kingdom 1796-1999. Cambridge, MA: National Bureau of Economic Research, 2001.

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12

Galí, Jordi. Technology, employment and the business cycle: Do technology shocks explain aggregate fluctuations?. London: Centre for Economic Policy Research, 1996.

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13

Galí, Jordi. Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? Cambridge, MA: National Bureau of Economic Research, 1996.

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14

Khan, Aubhik. Idiosyncratic shocks and the role of nonconvexities in plant and aggregate investment dynamics. Cambridge, Mass: National Bureau of Economic Research, 2007.

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15

Khan, Aubhik. Idiosyncratic shocks and the role of nonconvexities in plant and aggregate investment dynamics. Philadelphia, PA: Federal Reserve Bank of Philadelphia, 2004.

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16

Khan, Aubhik. Idiosyncratic shocks and the role of nonconvexities in plant and aggregate investment dynamics. [Minneapolis, Minn.]: Federal Reserve Bank of Minneapolis, 2004.

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17

Francis, Neville. Is the technology-driven real business cycle hypothesis dead?: Shocks and aggregate fluctuations revisited. Cambridge, MA: National Bureau of Economic Research, 2001.

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18

Mertens, Karel. Empirical evidence on the aggregate effects of anticipated and unanticipated U.S. tax policy shocks. Cambridge, MA: National Bureau of Economic Research, 2010.

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19

Commander, Simon. Output decline in Hungary and Poland in 1990-91: Structural change and aggregate shocks. Washington, D.C. (1818 H St., NW, Washington 20433): Economic Development Institute and the Country Economics Dept., World Bank, 1992.

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20

Galí, Jordi. Technology shocks and aggregate fluctuations: How well does the RBC model fit postwar U.S. data? Cambridge, Mass: National Bureau of Economic Research, 2004.

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21

Blanchard, Olivier. The role of shocks and institutions in the rise of European unemployment: The aggregate evidence. Cambridge, MA: National Bureau of Economic Research, 1999.

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22

Galí, Jordi. Technology shocks and aggregate fluctuations: How well does the rbs model fit postwar U.S. data? Cambridge, MA: National Bureau of Economic Research, 2004.

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23

Pessino, Carola. From aggregate shocks to labor market adjustments: Shifting of wage profiles under hyperinflation in Argentina. Buenos Aires, Argentina: Centro de Estudios Macroeconómicos de Argentina, 1993.

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24

Galí, Jordi. Technology shocks and aggregate fluctuations: How well does the real business cycle model fit postwar U.S. data? [Washington, D.C]: International Monetary Fund, Western Hemisphere Dept., 2004.

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25

Presley, John R. Real business cycles: Sectoral versus aggregate shocks and the elasticity of demand for income in terms of work effort. Loughborough: Loughborough University of Technology, Department of Economics, 1993.

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26

McGrattan, Ellen R. Comment on Gali and Rabanal's "technology shocks and aggregate fluctuations; how well does the RBC model fit postwar U.S. data?". [Minneapolis, Minn.]: Federal Reserve Bank of Minneapolis, 2004.

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27

Funke, M. Shock hunting: The relative importance of industry-specific region-specific and aggregate shocks in the OECD countries. London Business School, 1997.

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28

Andrle, Michal, Andrew Berg, Enrico Berkes, R. Armando Morales, Rafael Portillo, and Jan Vlcek. Do Money Targets Matter for Monetary Policy in Kenya? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198785811.003.0016.

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The framework in Chapter 15 is extended to incorporate an explicit role for money aggregates, with an application to Kenya. The chapter provides a general specification that can nest various types of money targeting (ranging from targets based on optimal money demand forecasts to those derived from simple money growth rules), interest-rate based frameworks, and intermediate cases. A novel interpretation of target misses in terms of structural shocks (aggregate demand, policy, shocks to money demand, etc.) is presented. In the case of Kenya, the authors find that: (i) the setting of money targets is consistent with money demand forecasting, (ii) targets have not played a systematic role in monetary policy, and (iii) target misses mainly reflect shocks to money demand. Simulations of the model under alternative policy specifications show that the stronger the ex post target adherence, the greater the macroeconomic volatility.
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29

Ferreira, Francisco H. G., and Norbert Schady. Aggregate Economic Shocks, Child Schooling And Child Health. The World Bank, 2008. http://dx.doi.org/10.1596/1813-9450-4701.

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30

Grigoli, Francesco, Damiano Sandri, and Emiliano Luttini. Idiosyncratic Shocks and Aggregate Fluctuations in an Emerging Market. International Monetary Fund, 2021.

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31

Grigoli, Francesco, Damiano Sandri, and Emiliano Luttini. Idiosyncratic Shocks and Aggregate Fluctuations in an Emerging Market. International Monetary Fund, 2021.

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32

Grigoli, Francesco, Damiano Sandri, and Emiliano Luttini. Idiosyncratic Shocks and Aggregate Fluctuations in an Emerging Market. International Monetary Fund, 2021.

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33

Cho, Jonghwa. An analysis of the real effects of money growth shocks and aggregate supply shocks. 1986.

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34

Artuc, Erhan. PPML Estimation of Dynamic Discrete Choice Models with Aggregate Shocks. The World Bank, 2013. http://dx.doi.org/10.1596/1813-9450-6480.

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35

Gal, Jordi, and Pau Rabanal. Technology Shocks and Aggregate Fluctuations: How Well Does the Rbc Model Fit Postwar U. S. Data? International Monetary Fund, 2004.

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36

Gal, Jordi, and Pau Rabanal. Technology Shocks and Aggregate Fluctuations: How Well Does the Rbc Model Fit Postwar U. S. Data? International Monetary Fund, 2004.

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37

Gal, Jordi, and Pau Rabanal. Technology Shocks and Aggregate Fluctuations: How Well Does the Rbc Model Fit Postwar U. S. Data? International Monetary Fund, 2004.

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38

Aggregate fluctuations from independent sectoral shocks: Self-organized criticality in a model of production and inventory dynamics. Cambridge, Mass: National Bureau of Economic Research, 1992.

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39

Senik, Claudia. Wealth and Happiness. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803720.003.0004.

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Does wealth accumulation impact subjective well-being? Within a country, household wealth has been shown to improve individual well-being by providing a safety net of protection against negative income shocks, by allowing current and expected consumption flows, and by its potential use as a collateral. At the aggregate level, direct evidence about the relationship between national wealth and happiness is almost non-existent, owing to data limitations and statistical identification problems. However, aggregate wealth impacts well-being indirectly, via positive channels such as institutional quality and improvement in health, life expectancy, and education. Wealth also brings about negative environmental degradations and other damages. The stock of accumulated wealth is also likely to affect happiness indirectly, via its influence on the rate of GDP growth, because both the level of income flows and the rate of income growth have been shown to be factors of higher well-being.
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40

Ragsdale, Lyn, and Jerrold G. Rusk. Campaign Context, Uncertainty, and Nonvoting. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190670702.003.0004.

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Abstract: The chapter introduces the specific indicators of uncertainty in the national campaign context, which include economic volatility, technology shock (with the invention of new mass communication devices, including radio, television, cable television, and the Internet), dramatic national events such as US involvement in major international conflicts, and federal expansion of the franchise. The more change in each indicator, the greater the increase in uncertainty. The increase in uncertainty produces a decrease in nonvoting. Conversely, the more stable the indicator, the less uncertainty and the more likely nonvoting increases. The chapter tests an aggregate model across the full time frame from 1920 through 2012 for presidential and midterm House elections. The results show that relative to such personal factors as age and education, measures of economic volatility, new communication technology, and visible national events decrease nonvoting in both presidential and midterm House elections.
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41

Brownbridge, Martin, and Louis Kasekende. Inflation Targeting in Uganda. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198785811.003.0002.

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The Bank of Uganda introduced an inflation targeting (IT) monetary policy framework in 2011, replacing a decades-old money targeting framework. This chapter reviews Uganda’s experience and concludes that an IT framework is feasible for Uganda, despite shallow financial markets, volatile exchange rates, supply price shocks which make inflation more volatile and difficult to forecast, and lack of data. Key prerequisites were the operational independence of the central bank and the primacy of the core inflation objective for monetary policy. The successful adoption of IT in Uganda depended on the adoption of a set of basic principles, including: the primacy of the inflation forecast in setting policy; the separation of monetary from fiscal operations; the adoption of a short-term interest rate as the sole operating target, rather than e.g. a mix of interest rates and monetary aggregates; and an emphasis on clear communications.
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