- ECONOMETRIA 126
- MODELOS ECONOMETRICOS 67
- ANALISIS DE REGRESION 22
- ANALISIS DE SERIES TEMPORALES 22
- ECONOMETRIA APLICADA 20
- ANALISIS ECONOMETRICO 18
- ECONOMIA MATEMATICA 18
- MODELOS MATEMATICOS 18
- INFERENCIA ESTADISTICA 17
- ECUACIONES SIMULTANEAS 14
- PROBABILIDADES 12
- MATRICES 11
- MODELO DE REGRESION 11
- CONDICIONES ECONOMICAS 10
- ESTADISTICA MATEMATICA 10
- MODELO DE PANEL 9
- MODELO LINEAL 9
- Estadística 8
- POLITICA ECONOMICA 8
- VARIABLES 8
- EJERCICIOS 7
- ENSAYO 7
- ESTUDIOS DE CASOS 7
- MODELOS ECONOMICOS 7
- PROCESO ESTOCASTICO 7
- REGRESION LINEAL 7
- MACROECONOMIA 6
- OPTIMIZACION 6
- SERIES TEMPORALES 6
- Statistics 6
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Are national transfers crowding out provincial tax revenues in Argentina?
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Lecturas de econometría /
Published 1972Table of Contents: “…La misión futura de la Econometric Society en la estadística internacional -- 2. …”
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Exchange rate misalignment : concepts and measurement for developing countries
Published 1999Table of Contents: “…Long-Run real exchange rate changes in developing countries: simulations from an econometric model / Nadeem Ul haque and Peter J. Montiel -- 10. …”
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An introduction to efficiency and productivity analysis /
Published 2005Table of Contents: “…2: REVIEW OF PRODUCTION ECONOMICS 2.1 Introduction 2.2 Production Functions 2.3 Transformation Functions 2.4 Cost Functions 2.5 Revenue Functions 2.6 Profit Functions 2.7 Conclusions. 3: PRODUCTIVITY AND EFFICIENCY MEASUREMENT CONCEPTS 3.1 Introduction 3.2 Set Theoretic Representation of a Production Technology 3.3 Output and Input Distance Functions 3.4 Efficiency Measurement using Distance, Cost and Revenue Functions 3.5 Measuring Productivity and Productivity Change 3.6 Conclusions. 4: INDEX NUMBERS AND PRODUCTIVITY MEASUREMENT 4.1 Introduction 4.2 Conceptual Framework and Notation 4.3 Formulae for Price Index Numbers 4.4 Quantity Index Numbers 4.5 Properties of Index Numbers: The Test Approach 4.6 The Economic-Theoretic Approach 4.7 A Simple Numerical Example 4.8 Tansitivity in Multilateral Comparisons 4.9 TFP Change Measurement Using Index Numbers 4.10 Empirical Application: Australian National Railways 4.11 Conclusions. 5: DATA AND MEASUREMENT ISSUES 5.1 Introduction 5.2 Outputs 5.3 Inputs 5.4 Prices 5.5 Comparisons over time 5.6 Output aggregates for sectoral and economy-wide comparisons 5.7 Cross-country comparisons of productivity 5.8 Data editing and errors 5.9 Conclusions. 6: DATA ENVELOPMENT ANALYSIS 6.1 Introduction 6.2 The Constant Returns to Scale DEA Model 6.3 The Variable Returns to Scale Model and Scale Efficiencies 6.4 Input and Output Orientations 6.5 Conclusions. 7: ADDITIONAL TOPICS ON DATA ENVELOPMENT ANALYSTS 7.1 Introduction 7.2 Price Information and Allocative Efficiency 7.3 Non-Discretionary Variables 7.4 Adjusting for the Environment 7.5 Input Congestion 7.6 Treatment of Slacks 7.7 Additional Methods 7.8 Empirical Application: Australian Universities 7.9 Conclusions. 8: ECONOMETRIC ESTIMATION OF PRODUCTION TECHNOLOGIES 8.1 Introduction 8.2 Production, Cost and Profit Functions 8.3 Single Equation Estimation 8.4 Imposing Equality Constraints 8.5 Hypothesis Testing 8.6 Systems Estimation 8.7 Inequality Constraints 8.8 The Bayesian Approach 8.9 Simulation Methods 8.10 Conclusion. 9: STOCHASTIC FRONTIER ANALYSIS 9.1 Introduction 9.2 The Stochastic Production Frontier 9.3 Estimating the Parameters 9.4 Predicting Technical Efficiency 9.5 Hypothesis Testing 9.6 Conclusions. 10: ADDITIONAL TOPICS ON STOCHASTIC FRONTIER ANALYSIS 10.1 Introduction 10.2 Distance Functions 10.3 Cost Frontiers 10.4 Decomposing Cost Efficiency 10.5 Scale Efficiency 10.6 Panel Data Models 10.7 Accounting for the Production Environment 10.8 The Bayesian Approach 10.9 Conclusions. 11: THE CALCULATION AND DECOMPOSITION OF PRODUCTIVITY CHANGE USING FRONTIER METHODS 11.1 Introduction 11.2 The Malmquist TFP Index and Panel Data 11.3 Calculation using DEA Frontiers 11.4 Calculation using SFA Frontiers 11.5 An Empirical Application 11.6 Conclusions. 12: Conclusions 12.1 Summary of Methods 12.2 Relative Merits of the Methods 12.3 Some Final Points Appendix 1: Computer Software Appendix 2: Philippines Rice Data References Author Index Subject Index…”
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Trade Openness and Income Inequality: A Panel Analysis of Latin American Countries (1990-2016)
Published 2020“…The effect of trade openness are robust to alternative econometric models, the inclusion of several control variables such as inflation, real GDP per capita, economic growth, the workforce skill level and the real effective exchange rate, as well as two alternative indicators of trade openness, the openness index, whose utilization is widespread in the literature, and the average tariff level. …”
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250
Estimation of Elasticities of Different Dairy Products in the Provinces of Santa Fe and Entre Ríos
Published 2008“…The methodology is derived from the application of an econometric LinQuad model which includes economic as well as demographic variables. …”
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251
The education networks of Latin America. Effects on bilateral trade during and after the cold war
Published 2021Get full text
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252
The economic impact of the creation of universities: evidence linked to the expansion of the education system in Argentina 1993-2018
Published 2022“…In this paper, an autoregressive spatial econometric model is used for panel data, with the aim of determining the regional economic impact on the regional geographic product (PGR) that the population level has and the creation of public management universities in Argentina, to the period 1993 – 2018. …”
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253
Estimating and Projecting Credit Portfolio Quality Using Macroeconomic Variables: A Study for Venezuela
Published 2007“…This study presents an econometric estimation of the impact of several macroeconomic aggregates on the level of non-performing loans in the Venezuelan banking system. …”
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254
Economic activity and the terms of trade. Argentina, a case study
Published 2021Get full text
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255
Mixed logistic model with two independent random coefficients for financial crisis prediction: argentinean companies
Published 2024Get full text
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256
Price elasticity of demand for urban public transport: An analysis for bus and underground services of the Autonomous City of Buenos Aires
Published 2016“…In the case of the subway, where more explanatory variables are available, both econometric methods generate negative own price-elasticities between 0.1 and 0.2. …”
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