What would Nelson and Plosser find had they used panel unit root tests?

In this study, we systemically apply nine recent panel unit root tests to the same fourteen macroeconomic and financial series as those considered in the seminal paper by Nelson and Plosser (1982). The data cover OECD countries from 1950 to 2003. Our results clearly point out the difficulty that applied econometricians would face when they want to get a simple and clear-cut diagnosis with panel unit root tests. We confirm the fact that panel methods must be very carefully used for testing unit roots in macroeconomic or financial panels. More precisely, we find mitigated results under the cross-sectional independence assumption, since the unit root hypothesis is rejected for many macroeconomic variables. When international cross-correlations are taken into account, conclusions depend on the specification of these cross-sectional dependencies. Two groups of tests can be distinguished. The first group tests are based on a dynamic factor structure or an error component model. In this case, the non stationarity of common factors (international business cycles or growth trends) is not rejected, but the results are less clear with respect to idiosyncratic components. The second group tests are based on more general specifications. Their results are globally more favourable to the unit root assumption.Panel Unit Root Tests

Network effects of the productivity of infrastructure in developing countries

Using panel data models, the author examines the threshold effects of the productivity of infrastructure investment in developing countries. He considers various specifications of an augmented production function that allow for endogenous thresholds. More precisely, these specifications are tested in a panel threshold regression model. The author's main robust result is the presence of strong threshold effects in the relationship between output and private and public inputs. Whatever the transition mechanism used, the testing procedures lead to strong rejection of the linearity of this relationship. In particular, the productivity of infrastructure investment generally exhibits some network effects. When the available stock of infrastructure is very low, investment in this sector has the same productivity as noninfrastructure investment. On the contrary, when a minimum network is available, the marginal productivity of infrastructure investment is generally largely greater than the productivity of other investment. Finally, when the main network is achieved, its marginal productivity becomes similar to the productivity of other investment.Economic Theory&Research,Investment and Investment Climate,Public Sector Economics&Finance,Non Bank Financial Institutions,Technology Industry

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

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.http://deepblue.lib.umich.edu/bitstream/2027.42/39967/3/wp581.pd

Backtesting VaR Accuracy: A New Simple Test

This paper proposes a new test of Value at Risk (VaR) validation. Our test exploits the idea that the sequence of VaR violations (Hit function) - taking value 1-α, if there is a violation, and -α otherwise - for a nominal coverage rate α verifies the properties of a martingale difference if the model used to quantify risk is adequate (Berkowitz et al., 2005). More precisely, we use the Multivariate Portmanteau statistic of Li and McLeod (1981) - extension to the multivariate framework of the test of Box and Pierce (1970) - to jointly test the absence of autocorrelation in the vector of Hit sequences for various coverage rates considered as relevant for the management of extreme risks. We show that this shift to a multivariate dimension appreciably improves the power properties of the VaR validation test for reasonable sample sizes.Value-at-Risk; Risk Management; Model Selection

Are Public Investment Efficient in Creating Capital Stocks in Developing Countries?

In many poor countries, the problem is not that governments do not invest, but that these investments do not create productive capital. So, the cost of public investments does not correspond to the value of the capital stocks. In this paper, we propose an original non parametric approach to evaluate the efficiency function that links variations (net of depreciation) of stocks to public investments. We consider four sectors (electricity, telecommunications, roads and railways) of two Latin American countries (Mexico and Colombia). We show that there is a large discrepancy between the amount of investments and the value of increases in stocks.Public Capital | Capital Stocks | Developing Countries

Are Public Investment Efficient in Creating Capital Stock in Developing Countries?.

In many poor countries, the problem is not that governments do not invest, but that these investments do not create productive capital. So, the cost of public investments does not correspond to the value of the capital stocks. In this paper, we propose an original non parametric approach to evaluate the efficiency function that links variations (net of depreciation) of stocks to public investments. We consider four sectors (electricity, telecommunications, roads and railways) of two Latin American countries (Mexico and Colombia). We show that there is a large discrepancy between the amount of investments and the value of increases in stocks.Developing Countries; Capital Stocks; Public Capital;

Threshold Effects of the Public Capital Productivity : An International Panel Smooth Transition Approach

Using a non linear panel data model we examine the threshold effects in the productivity of the public capital stocks for a panel of 21 OECD countries observed over 1965-2001. Using the so-called "augmented production function" approach, we estimate various specifications of a Panel Smooth Threshold Regression (PSTR) model recently developed by Gonzalez, Teräsvirta and Van Dijk (2004). One of our main results is the existence of strong threshold effects in the relationship between output and private and public inputs : whatever the transition mechanism specified, tests strongly reject the linearity assumption. Moreover this model allows cross-country heterogeneity and time instability of the productivity without specification of an ex-ante classification over individuals. Consequently it is posible to give estimates of productivity coefficients for both private and public capital stocks at any time and for each countries in the sample. Finally we proposed estimates of individual time varying elasticities that are much more reasonable than those previously published.Public Capital ; Panel Smooth ; Threshold Regression Models

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

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.monetary standard and regimes, non-stationarity and cointegration, transition, Poland.

Financial Development and Growth: A Re-Examination using a Panel Granger Causality Test

In this paper we investigate the causal relationship between financial development and economic growth. We use an innovative econometric method which is based on a panel test of the Granger non causality hypothesis. We implement various tests with a sample of 63 industrial and developing countries over the 1960-1995 and 1960-2000 periods. We use three standard indicators of financial development. The results provide support for a robust causality relationship from economic growth to the financial development. On the contrary, the non causality hypothesis from financial development indicators to economic growth can not be rejected in most of the cases. However, these results only imply that, if such a relationship exists, it can not be easily identified in a simply bi-variate Granger causality test.Granger Causality Tests; Panel Data; Financial Development; Economic Growth

How to Estimate Public Capital Productivity?

We propose an evaluation of the main empirical approaches used in the literature to estimate the contribution of public capital stock to growth and private factors' productivity. Our analysis is based on the replication of these approaches on pseudo-samples generated using a stochastic general equilibrium model, built as to reproduce the main long-run relations observed in US post-war historical data. The results suggest that the production function approach may not be reliable to estimate this contribution. In our model, this approach largely overestimates the public capital elasticity, given the presence of a common stochastic trend shared by all non-stationary inputsInfrastructures, Public capital, Cointegrated regressors..