The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank

Estrella, Arturo; Mishkin, Frederic S.

doi:10.1016/s0014-2921(96)00050-5

Cited by 378 publications

(292 citation statements)

References 15 publications

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“…As noted in Estrella and Mishkin (1997) the construction of a binary variable implies that one abstracts from the magnitude of the change in the dependent variable caused by a change in one of the independent variables and one focuses on a simple binary indicator. Instead of focussing on 'how much' emissions decrease as income grows, a binary indicator analyses 'if' that has been the case.…”

Section: A Binary Response Model To Test the Iermentioning

confidence: 99%

“…Instead of focussing on 'how much' emissions decrease as income grows, a binary indicator analyses 'if' that has been the case. Although one can argue that these models are less precise as they are unable to determine the actual magnitude, they are less demanding which may increase their potential accuracy (Estrella and Mishkin, 1997).…”

Section: A Binary Response Model To Test the Iermentioning

confidence: 99%

See 1 more Smart Citation

The income–environment relationship: Evidence from a binary response model

Verbeke

Clercq

2006

Ecological Economics

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The empirical environmental Kuznets curve (EKC) literature is vast but far from conclusive.Many authors have analysed the existence of an EKC for various pollutants. Others have used the EKC framework to identify country characteristics that help to explain the incomeenvironment relationship. In this framework environmental degradation is analysed using a second or third order polynomial in income and a limited number of control variables.Some authors question whether this standard framework is appropriate. This paper proposes an alternative to study the specific characteristics of countries that have experienced economic growth and an improving environment at the same time. We estimate a binary response model and find an EKC-like relation between the probability that a country's environment improves with economic growth and per capita GDP. Our evidence further suggests that the level of environmental damage is an important explanatory variable. We also confirm the importance of an open political system. These results indicate that the binary response model could be a valuable alternative to test which country specific characteristics are associated with a negative IER.

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Section: A Binary Response Model To Test the Iermentioning

confidence: 99%

Section: A Binary Response Model To Test the Iermentioning

confidence: 99%

The income–environment relationship: Evidence from a binary response model

Verbeke

Clercq

2006

Ecological Economics

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“…1 In contrast, empirical studies try to directly model the relationships between bond yields and macro variables by using Vector Autoregressive (VAR) models. Studies like Estrella and Mishkin (1997) and Evans and Marshall (1998) use VAR's with yields of various maturities together with macro variables. These studies infer the relationships between yield movements and shocks in macro variables using impulse responses (IR's) and variance decomposition techniques implied from the VAR.…”

Section: Introductionmentioning

confidence: 99%

A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables

Ang

Piazzesi

2003

Journal of Monetary Economics

1,297

325

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We describe the joint dynamics of bond yields and macroeconomic variables in a Vector Autoregression, where identifying restrictions are based on the absence of arbitrage. Using a term structure model with inflation and economic growth factors, together with latent variables, we investigate how macro variables affect bond prices and the dynamics of the yield curve. We find that the forecasting performance of a VAR improves when no-arbitrage restrictions are imposed and that models with macro factors forecast better than models with only unobservable factors.Variance decompositions show that macro factors explain up to 85% of the variation in bond yields. Macro factors primarily explain movements at the short end and middle of the yield curve while unobservable factors still account for most of the movement at the long end of the yield curve.

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“…This reasoning is contrary to the explanation of the effect of a short-term spread like 6TFF, which represents short-term market expectations about inflation/economic activity to which the FOMC does react. Estrella and Mishkin (1997) also find different predictive natures of spreads with different maturities with regard to forecasting inflation and output growth. Mishkin (1990a,b) discusses similar issues as well.…”

Section: Estimation Resultsmentioning

confidence: 94%

“…However, we can interpret this variable as a proxy for long-run inflation expectations, as pointed out in, e.g., Estrella and Mishkin (1997). As such, it may not be a variable the FOMC reacts upon directly, but it rather measures market expectations of what the FOMC will decide at upcoming meetings and what the long run impact of its decisions will be.…”

Section: Estimation Resultsmentioning

confidence: 99%

Bayesian forecasting of federal funds target rate decisions

Hauwe

Paap

Dijk

2013

Journal of Macroeconomics

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The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank

Cited by 378 publications

References 15 publications

The income–environment relationship: Evidence from a binary response model

The income–environment relationship: Evidence from a binary response model

A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables

Bayesian forecasting of federal funds target rate decisions

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