Mikael Juselius

Testing the New Keynesian Model on U.S. And Euro Area Data

I apply the Johansen and Swensen (1999, 2004) method of testing exact rational expectations within the cointegrated VAR (Vector Auto-Regressive) model, to testing the New Keynesian (NK) model. This method permits the testing of rational expectation systems, while allowing for non-stationary data. The NK-model is tested on quarterly U.S. and Euro area time series data. I find that the restrictions implied by the core equations of the NK-model are rejected regardless of sample periods or measures of real marginal costs. I also provide a tentative explanation of the results favored by previous researches.

Sustainable Financial Obligations and Crisis Cycles

The ability to distinguish between sustainable and excessive debt developments is crucial for securing economic stability. By studying US private sector credit loss dynamics, we show that this distinction can be made based on a measure of the incipient aggregate liquidity constraint, the financial obligations ratio. Specifically, as this variable rises, the interaction between credit losses and the business cycle increases, albeit with different intensity depending on whether the problems originate in the household or the business sector. This occurs 1–2 years before each recession in the sample. Our results have implications for macroprudential policy and countercyclical capital-buffers.

The Relevant Market for Production and Wholesale of Electricity in the Nordic Countries: An Econometric Study

We apply cointegration analysis to daily averages of Nord Pool prices covering the period 2001-2007 in order to empirically characterize the geographical dimension of the relevant market for production and wholesale of electricity. We reach the following econometric conclusions: (i) price areas Finland, Sweden, and Norway 3 unambiguously belong to the same relevant market; (ii) Denmark 2 belongs to this same market except for the subsample 2004-2007; (iii) Norway 1 and Denmark 1 define separate markets on their own. We find that the stochastic trends in Nord Pool prices originate in countries abundant in capacity to generate hydro power.

Testing Steady-State Restrictions of Linear Rational Expectations Models When Data are Highly Persistent

Steady-state restrictions are commonly imposed on highly persistent variables to achieve stationarity prior to confronting rational expectations models with data. However, the resulting steady-state deviations are often surprisingly persistent indicating that some aspects of the underlying theory may be empirically problematic. This paper discusses how to formulate steady-state restrictions in rational expectations models with latent forcing variables and test their validity using cointegration techniques. The approach is illustrated by testing steady-state restrictions for alternative specifications of the New Keynesian model and shown to be able to discriminate between different assumptions on the sources of the permanent shocks.

Do Markup Dynamics Reflect Fundamentals or Changes in Conduct

Persistent shifts in equilibria are likely to arise in oligopolistic markets and may be detrimental to the measurement of conduct, related markups and intensity of competition. We develop a cointegrated VAR (vector autoregression) based approach to detect long-run changes in conduct when data are difference stationary. Importantly, we separate the components in markups which are exclusively related to long-run changes in conduct from those explained solely by fundamentals. Our approach does not require estimation of markups and conduct directly, thereby avoiding complex problems in existing methodologies related to multiple and changing equilibria. Results from applying the model to US and five major European banking sectors indicate substantially different behavior of conventional raw markups and conduct-induced markups.

Cointegration implications of linear rational expectation models

This paper derives the cointegration spaces that are implied by linear rational expectations models when data are I(1). The cointegration implications are easy to calculate and can be readily applied to test if the models are consistent with the long-run properties of the data. However, the restrictions on cointegration only form a subset of all the cross-equation restrictions that the models place on data. The approach is particularly useful in separating potentially data-consistent models from the remaining models within a large model family. Moreover, the approach provides useful information on the empirical shock structure of the data.