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Modeling Georgia
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Baksa, D. ; Bečičková, Hana ; Daniš, P. ; Hřebíček, Hynek ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lukáč, J. ; Mirzoyan, Armen ; Motl, Tomáš ; Musil, K. ; Plotnikov, S. ; Remo, A. ; Szilágyi, K. ; Vlček, J.
The report has two chapters. Chapter 1 describes the structural model which lies at heart of the FPAS. It summarizes the main features of the Georgian economy relevant for building the structural model and describes in detail the most distinctive parts of the model. The chapter concludes with an analysis of the model properties and an interpretation of past economic developments in Georgia through the optic of the model. Chapter 2 evaluates how the FPAS performs empirically. The forecasting power is assessed by in-sample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison.
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Modeling Cambodia
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Bečičková, H. ; Daniš, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lamazoshvili, Beka ; Lukáč, J. ; Menkyna, Robert ; Mirzoyan, Armen ; Motl, T. ; Musil, K. ; Plotnikov, S. ; Rasulova, Khanifakhon ; Remo, A. ; Vlček, J.
The report consists of three chapters. Chapter 1 presents the structural macroeconomic model, its changes compared to the June 2010 version, and its properties captured by impulse-response functions and by variance decompositions of the model’s variables in terms of the model’s shocks. What is important is the part on the model-consistent interpretation of the recent economic history of Cambodia. The section describing Bayesian vector autoregressions used for the near-term forecasting concludes. Chapter 2 evaluates how the models perform empirically. The forecasting power is assessed using both within-sample and out-of-sample comparisons with the random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison. The last chapter provides an overview of the considerable country database that has been compiled.
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Modeling Mozambique
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Bečičková, H. ; Daniš, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lamazoshvili, Beka ; Lukáč, J. ; Menkyna, Robert ; Mirzoyan, Armen ; Motl, T. ; Musil, K. ; Plotnikov, S. ; Rasulova, Khanifakhon ; Remo, A. ; Vlček, J.
The report has four chapters. Chapter 1 summarizes the main features of the Mozambican economy relevant for building the FPAS. Chapter 2 presents the structural macroeconomic model and its properties, captured by the decompositions of the variances of the model’s variables in terms of the model shocks and by the model’s impulse-response functions. This chapter also describes the Bayesian vector autoregressions used for near-term forecasting. Chapter 3 evaluates how the models perform empirically. The forecasting power is assessed both in the sample and by using an out-of-the-sample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison. Chapter 4 summarizes the data used in the structural model and the issues identified during the data collection process.
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Modeling Kenya
Auda, O. ; Bečičková, H. ; Cincibuch, M. ; Čižmár, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kameník, O. ; Katreniaková, D. ; Kejak, Michal ; Lamazoshvili, Beka ; Lukáč, J. ; Machala, J. ; Menkyna, Robert ; Musil, K. ; Rasulova, Khanifakhon ; Remo, A. ; Vávra, D. ; Vlček, J. ; Zemčík, Petr
The report has three chapters. Chapter 1 summarizes the main features of the Kenyan economy relevant for building the FPAS. Chapter 2 presents the structural macroeconomic model and its properties captured by the decompositions of variances of the model’s variables in terms of the model shocks and by its impulse-response functions. This chapter also describes Bayesian vector autoregressions used for the near-term forecasting. Chapter 3 evaluates how the models perform empirically. The forecasting power is assessed both in the sample and by using an out-of-the-sample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison.
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Modeling Guatemala
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Bečičková, H. ; Daniš, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lamazoshvili, Beka ; Lukáč, J. ; Menkyna, Robert ; Mirzoyan, Armen ; Motl, T. ; Musil, K. ; Plotnikov, S. ; Rasulova, Khanifakhon ; Remo, A. ; Vlček, J.
The report consists of three chapters. Chapter 1 presents the structural macroeconomic model, its changes compared to the December 2009 version, and its properties captured by impulse-response functions and by variance decompositions of model’s variables in terms of the model shocks. Important is the part on the model-consistent interpretation of the recent economic history of Guatemala. The section describing Bayesian vector autoregressions used for the nearterm forecasting concludes. Chapter 2 evaluates how the models perform empirically. The forecasting power is assessed using both in-sample and out-of-sample comparisons with the random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison. The last chapter provides an overview of the considerable country database that has been compiled.
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Modeling Egypt
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Bečičková, H. ; Daniš, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lamazoshvili, Beka ; Lukáč, J. ; Menkyna, Robert ; Mirzoyan, Armen ; Motl, T. ; Musil, K. ; Plotnikov, S. ; Rasulova, Khanifakhon ; Remo, A. ; Vlček, J.
The report has three chapters. Chapter 1 summarizes the main features of the Egyptian economy relevant for building the FPAS. Chapter 2 presents the structural macroeconomic model and its properties captured by the decompositions of variances of the model’s variables in terms of the model shocks and by its impulse-response functions. This chapter also describes Bayesian vector autoregressions used for the near-term forecasting. Chapter 3 evaluates how the models perform empirically. The forecasting power is assessed both in the sample and by using an out-of-the-sample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison.
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Modeling Belarus
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Bečičková, H. ; Daniš, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lamazoshvili, Beka ; Lukáč, J. ; Menkyna, Robert ; Mirzoyan, Armen ; Motl, T. ; Musil, K. ; Plotnikov, S. ; Rasulova, Khanifakhon ; Remo, A. ; Vlček, J.
The report has three chapters. Chapter 1 presents the structural macroeconomic model, its changes compared to the May 2010 version, and its properties captured by impulseresponse functions and by variance decompositions of model’s variables in terms of the model shocks. Important is the part on the model-consistent interpretation of the recent economic history of Belarus. The section describing Bayesian vector autoregressions used for the near-term forecasting concludes. Chapter 2 evaluates how the models perform empirically. The forecasting power is assessed using both in-sample and out-of-sample comparisons with the random-walk benchmark. We conclude that the FPAS performs satisfyingly in this comparison. The last chapter provides an overview of the considerable country database that has been compiled.
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Modeling Armenia
Cincibuch, M. ; Kejak, Michal ; Vávra, D. ; Auda, O. ; Aslanyan, Gurgen ; Bečičková, H. ; Daniš, P. ; Hřebíček, H. ; Janjgava, Batlome ; Kacer, R. ; Kameník, O. ; Konopecký, F. ; Lamazoshvili, Beka ; Lukáč, J. ; Menkyna, Robert ; Mirzoyan, Armen ; Motl, T. ; Musil, K. ; Plotnikov, S. ; Rasulova, Khanifakhon ; Remo, A. ; Vlček, J.
The report has two chapters. Chapter 1 describes the structural model which lies at heart of the FPAS. It summarizes the main features of the Armenian economy relevant for building the structural model and describes in detail the most distinctive parts of the model. The chapter concludes with an analysis of the model properties and an interpretation of past economic developments in Armenia through the optic of the model. Chapter 2 evaluates how the FPAS performs empirically. The forecasting power is assessed by in-sample comparison with the standard random-walk benchmark. We conclude that the FPAS performs satisfactorily in this comparison.
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