Credit Market Disequilibrium in Poland: Can We Find What We Expect? Non-Stationarity and the 'Min' Condition

Abstract

This paper presents an empirical investigation of the disequilibrium hypothesis on the Polish loan market in the 1990s. Using data over this period of deep transition, we estimate a disequilibrium model with a standard maximum likelihood method. However, the estimates are highly counter-intuitive as regards the timing of the identified regimes. We show that the gap between the econometric evidence and the expected results may stem from the issue of stochastic non-stationarity in a disequilibrium setting based on the "min" condition. We find that the omission of one non-stationary variable of the cointegrating space or the absence of a "structural" cointegrating relationship in one or both regimes lead to a spurious configuration. In such a case, using, wrongly, the standard likelihood function, derived under the hypothesis of stationarity, may lead to non-convergent estimates of structural parameters and, as a consequence, to a fallacious regimes identification. Therefore, as the first approach to this issue, we estimate a disequilibrium model with stationary data. The empirical results are then robust and economically founded and correspond to the set and the timing of anticipated regimes.

Is There a Credit Crunch in the Czech Republic?

“…The credit supply function was modifi ed according to the empirical analysis provided by Vodová (2009) and the demand function was extended by the exchange rate which represent the specifi c conditions of small open economies (Arlt et al, 2001). As the second step we employed the provided by Hurlin and Kierzenkowski (2007) to identify disequilibrium in the credit market, especially excess of demand (credit crunch) or supply of new amounts of credit at the time t. To estimate the disequilibrium model we applied the full-information maximum likelihood approach with a numerical maximization of the likelihood function. We created 4 models where Model 3 and Model 4 are background accepted for discussion of the results.…”

“…Thus, the model (1) indicates the probability of each observation belonging to either supplied or demand amounts. However, due to the nonstationarity of data at levels we applied the model proposed by Hurlin and Kierzenkowski (2007), where growth rates correspond to the transformed data by fi rst order diff erences:…”

“…Maddala and Nelson (1974) contributed that the maximum likelihood method is appropriate for disequilibrium models, which has been used for empirical analysis of credit markets in diff erent countries. This methodological approach was applied to test the credit crunch hypothesis in diff erent countries across the world by Hancock and Wilcox (1998), Agénor, Aizenman, and Hoff maister (2004), Atanasova and Wilson (2004), Hurlin and Kierzenkowski (2007) and Poghosyan (2011).…”

Le financement des PME en Tunisie

“…C' est par la simple comparaison des valeurs convenables de la demande et de l'offre de crédit que les proportions d' entreprises rationnées sont mesurées. Les travaux pionniers de l'économétrie du déséquilibre visant à tester le rationnement du cré-dit (Laffont et Garcia, 1977 ;Sealey, 1979 ;Ito et Ueda, 1981) se sont traduits par un nombre croissant d' études des marchés du crédit en déséquilibre, par exemple : aux États-Unis (Perez, 1998), en Corée, au Japon (Ogawa et Suzuki, 2000), à Taïwan (Shen, 2002), au Royaume-Uni (Atanasova et Wilson, 2004), en Pologne ( Hurlin et Kierzenkowski, 2007) et en Belgique (Steijvers, 2008).…”

Merchant selection and pricing strategy for a platform firm in the online group buying market

“…The fixed supply case is considered by Hartley (1976) who uses endogenously determined prices. Applications of the market disequilibrium model include an analysis of the housing market (Riddel 2004), macroeconomics (Velupillai 2006), the credit market (Hurlin and Kierzenkowski 2007), and the corporate loan market (Atanasova and Wilson 2004). Our paper is the first study known to introduce market disequilibrium models into an analysis of the online group-buying market.…”