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Books on the topic 'Simultaneous equation models'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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1

Hall, Alastair. Estimation and inference in simultaneous equation models. [s.l.]: typescript, 1985.

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2

Evans, Lewis. Simulating dynamic simultaneous equation models using complete information. Wellington: Victoria University of Wellington, Department of Economics, 1985.

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3

Krishnakumar, Jayalakshmi. Estimation of simultaneous equation models with error components structure. Berlin: Springer Verlag, 1988.

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4

Krishnakumar, Jayalakshmi. Estimation of simultaneous equation models with error components structure. Berlin: Springer-Verlag, 1988.

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5

Krishnakumar, Jayalakshmi. Estimation of Simultaneous Equation Models with Error Components Structure. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-45647-3.

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6

Sims, Christopher A. MCMC method for Markov mixture simultaneous-equation models: A note. [Atlanta]: Federal Reserve Bank of Atlanta, 2004.

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7

Carpenter, Gregory S. A test for detecting and identifying unequal parameters in simultaneous-equation models. West Lafayette, Ind: Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1988.

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8

Hausman, Jerry A. Efficient estimation and identification of simultaneous equation models with covariance restrictions. Cambridge, Mass: Dept. of Economics, Massachusetts Institute of Technology, 1985.

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9

Ali, Mubarik. Supply response of major crops in Pakistan: A simultaneous equation approach. Islamabad: Directorate of Agricultural Policy and Chemonics International Consulting Divison for the Economic Analysis Network Project in collaboration with the Ministry of Food, Agriculture, and Cooperatives, Government of Pakistan, and the United States Agency for International Development, 1988.

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10

Pötter, Ulrich. Models for interdependent decisions over time. Colchester: European Science Foundation, Scientific Network on Household Panel Studies, University of Essex, 1992.

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11

Newey, Whitney K. Nonparametric estimation of triangular simultaneous equations models. Cambridge, Mass: Massachusetts Institute of Technology, 1998.

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12

Blundell, Richard. Estimation in the simultaneous equation Tobit model. London: University College, 1985.

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13

Shipp, Bernd. Minimax-Schätzer im simultanen Gleichungsmodell bei vollständiger und partieller Vorinformation. Frankfurt am Main: Anton Hain, 1990.

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14

Factors influencing hotel room supply and demand in Kenya: A simultaneous equations model. Nairobi, Kenya: Kenya Institute for Public Policy Research and Analysis, 2009.

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15

Yi, Qian. Investigating the dynamic effects of counterfeits with a random changepoint simultaneous equation model. Cambridge, MA: National Bureau of Economic Research, 2011.

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16

Krichene, Noureddine. A simultaneous equations model for world crude oil and natural gas markets. Washington, D.C: International Monetary Fund, African Dept., 2005.

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17

Dufour, Jean-Marie. Finite sample inference methods for simultaneous equations and models with unobserved and generated regressors. Bristol: University of Bristol, Department of Economics, 1999.

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18

Smith, Richard J. An exogeneity test for a simultaneous equation Tobit model with an application to labour supply. London: University College, 1985.

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19

Hodoshima, Jiro. Identification and estimation in linear simultaneous equations models with structural change under limited information: Gains by homoskedasticity. Louvain-la-Neuve: CORE, 1985.

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20

Rigobón, Roberto. Identification through heteroskedasticity: Measuring "contagion" between Argentinean and Mexican sovereign bonds. Cambridge, MA: National Bureau of Economic Research, 2000.

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21

Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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Abstract:
The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Detailed solutions of the examples in Excel and the R software environment are included. Meets the requirements of the federal state educational standards of higher education of the latest generation. For undergraduate and graduate students studying in the field of "Economics", the curriculum of which includes the disciplines "Econometrics"," Econometric Modeling","Econometric research".
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22

Miyajima, M. The municipal financial planning model: A simultaneous regression equations and goal programming approach. 1986.

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23

Mellander, Erik, and Leif Jansson. Conrad: A Maximum Likelihood Program for Estimation of Non-Linear Simultaneous Equations Models (Research Report (Nordic Africa Institute)). Coronet Books, 1987.

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