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Ludwig ID of RE Models under IF

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Ludwig ID of RE Models under IF

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFecent version: ww.julianfludwig.comAbstractIdentification of full information rational expectations (FIKE) models suiters from Manski's (1993) reflect

ion problem. 1 extend the standard rational expectations (KE) model to allow for a more general information structure and introduce a new framework to Ludwig ID of RE Models under IF

ident ify the generalized model wit h forecaster data. Identification is no longer subject to the reflection problem when two changes are made to the

Ludwig ID of RE Models under IF

information structure: the addition of news shocks ami imperfect information. News shocks provide additional variation in expectations hImiui the fut

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFne direction. Expectations data are consistent, wit h both. An application to Greenbook forecasts illustrates the importance of both news shocks ami l

earning about the past. When I apply this framework to a Blanchard and Quail (1989) dceoni|M>sit.ion. 1 reach qualitatively new results. For example, Ludwig ID of RE Models under IF

expansionary supply shocks decrease unemployment . Supply shocks are also particularly subject to both news and information rigidities, so relaxing th

Ludwig ID of RE Models under IF

e information structure is key to correctly identifying these shocks.Keywords: Expectations, Information Rigidity, News Shocks, Survey Forecasts J EL

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFS.A. Email: julian.hidwigXittu.edu. I am grateful to Olivier Coibion, Saroj Bhatt arai and llaiqing Xu for their invaluable guidance and support. 1 al

so benefited from conversations with Chi Zhang, Stefano Eusepi, Christoph Boehin, Tatevik Sekhposyan, Jessie Coe. Kevin Kuruc, Cooper How'S, Choongryu Ludwig ID of RE Models under IF

l Yang, Andrés Mendez Ruiz, ami Shaofei .Jiang as well as with many seminar participants from the University of Texas at Austin, and Texas A&M Univers

Ludwig ID of RE Models under IF

ity.1 IntroductionIn modern micro-founded macro models, t he decisions of economic agents are inherently forward-looking and therefore depend on their

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFels, it. becomes difficult to determine to what extent expectations affect actions and vice-versa. I relate this simultaneity to Manski's (1993) refle

ction problem and introduce a new way to deal with its implications for identification.The importance of expect ations has long been emphasized in rat Ludwig ID of RE Models under IF

ional expect ations (RE) models (see e.g. Lucas, 1972, 1976; Kydland and Prescott, 1982). This paper provides a new methodology to identify the param

Ludwig ID of RE Models under IF

eters of RE models using data on the expectations of economic agents at multiple horizons, specifically, I relax the full-information assumption and a

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFa. The resulting variation in expectations is no longer proportional to current actions so that identification is possible. This flexible information

st ruct lire brings together the literat ure on news shocks (see Beaudry and Portier, 20(11, 2006), where information arrives before impact, and the l Ludwig ID of RE Models under IF

iterature on information frictions (sec Mankiw and Reis, 2002: Woodford, 2003: Sims. 2003), where agents gather relevant, information only after the p

Ludwig ID of RE Models under IF

eriod is realized. Combining both dimensions is the key to identifying the parameters of the model.I relate the identification issue to Manski (1993),

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IF expectations are modelled simply as the average among individuals, the researcher cannot, distinguish whet her expectations change individual behavio

ur or if they simply reflect behaviour without causing it. 1 extend his proposition to show that full information rational expectations (FIRE) models Ludwig ID of RE Models under IF

suffer from the same type of reflection problem as well: since information is only gathered in one period, expectations about the future are proportio

Ludwig ID of RE Models under IF

nal to realizations today. The researcher can therefore not distinguish t he1direct effect of a shock OH the economy from the indirect effect of obser

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFpically derived from a micro-founded model. I provide a now way to deal with this identification issue by incorporating data on expectations at. multi

ple horizons and by relaxing the full information assumption.There are many ways to relax full information (FT). Mankiw and Reis (2002) introduce a st Ludwig ID of RE Models under IF

icky information approach where agents update their expectations infrequently, but when they update their expectations, they fully observe the state.

Ludwig ID of RE Models under IF

Woodford (2003) models information rigidities with a noisy information approach where agents receive noisy signals about, the state of the economy. Si

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IF information. The solution of this problem is characterized by rational inattention, where agents choose to deviate from full information. Models with

such information rigidities allow for information to arrive after the shocks are realized so that agents no longer fully observe the current state of Ludwig ID of RE Models under IF

the economy. Ill contrast, news shock models allow for information to arrive before the shock hits the economy. Beaudry and Portier (2001) introduce

Ludwig ID of RE Models under IF

news shocks as noisy signals about fut ure developments of t he economy, while Beaudry and Portier (2000), Davis (2007), and Christiano Ct al. (2010)

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFal information structure than what is allowed in standard macroeconomic models.The core identification property is that future outcomes only have an e

ffect, on today’s economy if agents observe these outcomes in advance. Hence, any fluctuations that are unobserved cannot be caused by future outcomes Ludwig ID of RE Models under IF

. These unobserved fluctuations are therefore fully backward-looking and can lie used to identify the effect of current on fut ure outcomes. Changes i

Ludwig ID of RE Models under IF

n expectat ions about t he previous period, defined as backcast revisions, collect these unobserved fluctuations. Hence, data on expectations about bo

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFer direction is identified when data on expectations about the next period is available. Civen the identified effect of current outcomes on expectatio

ns of future outcomes, the remaining variation in expectations of the next period must come from additional information (hat is obtained today about t Ludwig ID of RE Models under IF

he future. The effect of the remainder on current outcomes thus identifies the effect of expectations so that the forward-and backward-looking compone

Ludwig ID of RE Models under IF

nts of the RE model are identified. Key for identification is the timing assumption that expectations can only depend on information obtained up until

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IF and Pakcs. 1996; Blundell and Bond. 2000; Levinsolm and Petrin, 2003). To my knowledge, (his is the first paper that uses the variation generated by

relaxing full information to separately identify- the parameters governing the backward- and forward-looking dynamics of BE models.The proposed strate Ludwig ID of RE Models under IF

gy identifies the forward- and backward-looking components simultaneously, without imposing additional restrictions on the model equations. Instead of

Ludwig ID of RE Models under IF

imposing a particular structural model, this approach nests all models that, have the form of RE models with a flexible information structure. Hence,

Identification of Rational Expectations Models Under Information FrictionsJulian F. Ludwig* Texas Tech UniversitySeptember 19. 2019Link to the most re

Ludwig ID of RE Models under IFs are orthogonalized. Identification instead relies on the assumption that, data on expectations across horizons, both future and past, is available a

nd (hat this data correctly captures beliefs of agents. Moreover, identification requires a positive variance of backcast revisions, and nonoollineari Ludwig ID of RE Models under IF

ty between now- and forecasts, features which appear to be consistent wit h the data. Hence, I impose a completely different set of assumptions to ide

Ludwig ID of RE Models under IF

ntify the RE model than what is common in the literature.I implement the identification strategy using data on expectations from the Greenbook, a coll

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