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SummaryThe paper deals with the concept of identification in inferential statistics. At first a general concept of identification is defined and developed. Thereafter, the general theory is applied to univariate linear regression and simultaneous equation systems. Finally, attention is paid to models with lagged variables and some new related problems are suggested.

Intro -- Preface -- Contents -- Part I Fundamental Theory -- Validating Markov Switching VAR Through Spectral Representations -- 1 Introduction -- 2 Spectra of Markov Switching VAR -- 2.1 The Case of Hidden Markov Process -- 2.2 The Case of MS VAR(p) -- 3 Frequency Variability in Real Data -- 4 Conclusion -- References -- Rapid Optimal Lag Order Detection and Parameter Estimation of Standard Long Memory Time Series -- 1 Introduction -- 2 Preliminaries -- 2.1 Fractionally Differenced Long Memory Processes -- 3 State Space Representation of an ARFIMA Time Series -- 3.1 State Space Representation of ARFIMA Model -- 3.2 KF and Estimation Process -- 4 Simulation Results -- 5 Empirical Evidence -- 6 Concluding Remarks -- References -- Spatial Econometric Analysis: Potential Contribution to the Economic Analysis of Smallholder Development -- 1 Introduction -- 2 Advances in Data to Capture Spatial Heterogeneity -- 2.1 GIS and GPS Mapping -- 2.2 Big Data -- 2.3 Increased Availability of Panel Data Sets -- 3 Review of Existing Literature on Spatial Econometric Analysis of Smallholder Development -- 3.1 Recent Progress in Spatial Econometric Modelling -- 3.2 Use of Spatial Econometric Analysis to Study Spillovers and Spatial Interaction -- 3.3 Environmental and Land Use Applications -- 3.4 Accounting for Space in Analyses of Technology Adoption and Productivity -- 4 Potential Areas for Analysis Using Spatial Econometric Methods: Examples from the Philippines -- 4.1 Spatial Heterogeneity in the Rural Sector of the Philippines: Example of Rice Ecosystems -- 4.2 Assessment of Smallholder Response to Rural Development Interventions -- 4.3 Measuring, Decomposing and Explaining TFP Growth in Smallholder Farming -- 5 Prospects and Conclusions -- References -- Consistent Re-Calibration in Yield Curve Modeling: An Example -- 1 Introduction.

Fichier WP en ligne ; We propose a bootstrap-based test of the null hypothesis of equality of two firms' conditional Risk Measures (RMs) at a single point in time. The test can be applied to a wide class of conditional risk measures issued from parametric or semi-parametric models. Our iterative testing procedure produces a grouped ranking of the RMs which has direct application for systemic risk analysis. A Monte Carlo simulation demonstrates that our test has good size and power properties. We propose an application to a sample of U.S. financial institutions using CoVaR, MES, and SRISK, and conclude that only SRISK can be estimated with enough precision to allow for meaningful ranking.