INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted.
Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscri pt and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. ProQuest Information and Leaming 300 North Zeeb Road, Ann Arbor, MI 48106-1346 USA 800-521-0600 BOSTON UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES Dissertation AN INVESTIGATION INTO THE POSITIVE AND NORMATIVE ASPECTS OF MONETARY POLICY ADITI THAPAR B., University of Delhi, 1993 M., Delhi School of Economics, 1995 Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2003 UMI Number: 3067204 UMI ® UMI Microform 3067204 Copyright 2003 by ProQuest information and Learning Company.
All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest information and Learning Company 300 North Zeeb Road P. Box 1346 Ann Arbor, Mi 48106-1346 Approved by rofessor of Economics Second Reader <=: — S Simon Gilchrist, Ph.
Associate Professor of Economics on, " me ia. Third Reader U/ Otolay C6 CÁ Claudia Olivetti, Ph. Assistant Professor of Economics ACKNOWLEDGEMENTS There are many people without whom this dissertation would not have been possible. First and foremost, I would like to thank my advisers.
I am grateful to my first reader Russell Cooper for his help in getting me started on my dissertation, and for his generosity with his time. I am indebted to Simon Gilchrist without whose guidance and encouragement this dissertation would never have been completed. I would also like to thank Claudia Olivetti who read and commented on every draft of my dissertation, and was an invaluable source of suggestions, encouragement and support. Many frends deserve special thanks.
Chandana Singh who has always been there for me over the last two decades. Richa Sagar, Nandini Hadker, Asha Abraham, Eva Gutierrez, Shivnath Thukral and Aniket Singh have been an endless source of reassurance and comfort through graduate school. I am also grateful to my family. In particular, I would like to thank my parents, my grandmother, my brother and my sister for their love, support and their faith in my abilities.
Finally, I have to thank John Leahy. This dissertation could not have been completed without his love, encouragement, patience, and support. ill AN INVESTIGATION INTO THE POSITIVE AND NORMATIVE ASPECTS OF MONETARY POLICY (Order No. ) ADITI THAPAR Boston University Graduate School of Arts and Sciences, 2003 Major Professor: Russell Cooper, Professor of Economics ABSTRACT This dissertation consists of three chapters, each of which focuses on a different aspect of monetary policy.
In the first chapter, | develop a methodology that uses private forecasts of output, interest rates and prices to assess the effects of money on output and prices. | contrast the predictions of my model with the current practice that derives forecasts from a linear econometric model. The advantage of my methodology is that it is more likely to be robust to changes in policy regimes and to the exclusion of important information from the forecasting equations. I find that the two approaches yield broadly similar results concerning the effect of money on output, but that the effect of tight money on prices is positive when using the market-based shocks constructed from private forecasts.
In the second chapter, I present a theoretical analysis of the response of optimal monetary policy to productivity shocks. I develop a model in which money is used as the medium of exchange. I characterize the policy of a monetary authority that maximizes the welfare of its citizens, and analyze the implications of this policy for unemployment insurance. I IV find that monetary authorities tend to increase money supply when productivity increases.
This implies an insurance policy that is procyclical, the opposite of the standard counter-cyclical view of unemployment insurance. In the third chapter, I analyze the costs and benefits of monetary unions. I extend the model considered in chapter two to multiple-countries, and contrast the policies of national monetary authorities that maximize national welfare with those of a monetary union that maximizes the welfare of the union as a whole. I find that the national monetary authorities tend to create too much money.
Smaller or more open nations have a greater incentive to create money. I find that if the countries are not too dissimilar then the creation of a union increases welfare. TABLE OF CONTENTS List of Tables vũ List of Figures vill List of Abbreviations Chapter |: Using Private Forecasts to Estimate the Effects of Monetary Policy Chapter 2: Search and Money with Aggregate Uncertainty 49 Chapter 3: Welfare Effects of a Monetary Union in a Search Model with Money 79 References 131 Curriculum Vitae 136 LIST OF TABLES Table 1.2 Impulse response using the federal funds rate Table 1.3 Impulse response using the T-bill rate. Sample period: 1978-1995 45 Table 1.4 Impulse response using the T-bill rate.
Sample period: 1982-1995 46 Table 1.5 Impulse response using the commodity price index from the VAR 47 Table 1.6 Impulse response using the structural errors from the VAR 48 Table 3.1 Meeting Technology 102 Vil LIST OF FIGURES Figure 1.1(a) Comparison of the one quarter ahead forecast error on GDP and Deflator from the GB and SPF forecasts 34 Figure 1.1(b) Comparison of the two, three and four quarter ahead forecast error on GDP from the GB and SPF forecasts 35 Figure 1.l{c) Comparison of the two, three and four quarter ahead forecast error on Deflator from the GB and SPF forecasts 36 Figure 1.2(a) Comparison of the one quarter ahead forecast error on GDP from the SPF and VAR-1f forecasts 37 Figure 1.2(b) Comparison of the one quarter ahead forecast error on Deflator from the SPF and VAR-1f forecasts 37 Figure 1.3(a) Comparison of the federal funds rate and its forecast from the futures market and VAR-If 38 Figure 1.3(b) Reduced form error on federal funds rate 38 Figure 1.4(a) Comparison of the T-bill rate and its forecast from the futures market and VAR-It 39 Figure 1.4(b) Reduced form error on T-bill rate 39 Figure 1.5 Structural error on federal funds rate 40 Figure 1.6 Structural error on T-bill rate 40 Figure 1.7 Comparison of federal funds rate and T-bill rate 4] Figure 2.1 Impulse response functions with fixed monetary policy 77 Figure 2.2 Impulse response functions with flexible monetary policy 78 Vill Figure 3.1(a) Relation between Openness and Money 127 Figure 3.1(b) Net gain to Forming a Monetary Union 127 Figure 3.2(a) Net Gain in Welfare by Forming a Monetary Union 128 Figure 3.2 (b) Effect of Differences in Size on Money in Country 1 128 Figure 3.3(a) Welfare Gain to Country | by Forming a Union 129 Figure 3.3(b) Effect of Productivity Differences to Money in Country | 129 Figure 3.4 Impulse response functions 130 IX LIST OF ABBREVIATIONS Auto Regression BEA Bureau of Economic Analysis CBOT Chicago Board of Trade CME Chicago Mercantile Exchange FOMC Federal Open Market Committee GB Greenbook GB-f Results using Greenbook forecasts and the federal funds rate GB-t Results using Greenbook forecasts and 3-month U. Treasury bill rate GB-lt Results using Greenbook forecasts and the 3-month U. Treasury bill structural error from VAR-It GB-Pt Results using Greenbook forecasts and the 3-month U. Treasury bill structural error from VAR-Pt GDP Gross Domestic Product GMM Generalized Method of Moments Lid.
Identically and independently distributed Moving Average NAFTA North American Free Trade Agreement OLS Ordinary Least Squares SPF Survey of Professional Forecasters SPF-f Results using Survey of Professional Forecasters forecasts and the federal funds rate SPF-t Results using Survey of Professional Forecasters forecasts and the 3- month U. Treasury bill rate T-bill 3-month U. Treasury bil! Unemployment Insurance Policy US. United States VAR Vector Autoregression VAR-If VAR that includes log of GDP, log of Deflator and federal funds rate VAR-It VAR that includes log of GDP, log of Deflator and 3-month U.
Treasury bill rate VAR-Pf VAR that includes log of GDP, log of Deflator, log of the commodity price index and federal funds rate VAR-Pt VAR that includes log of GDP, log of Deflator, log of the commodity price index and 3-month U. Treasury bill rate xi 1 Chapter 1: Using Private Forecasts to Estimate the Effects of Monetary Policy 1.1 Introduction Questions concerning the effect of money on output and inflation lie at the heart of macroeconomics. The key step in any analysis of the monetary transmission mechanism is the identification of exogenous shocks to monetary policy. Current practice involves fitting a linear model, called a Vector Autoregression or VAR, to the data to identify monetary shocks off of the models forecast errors.
the appropriateness of the VAR methodology has come into question. The most common criticisms are its time-invariant linear structure and the low correlation between the forecasts generated by the VAR and those generated by efficient markets. In this paper I identify the effects of monetary policy using the forecast errors of market participants rather than an econometric model. My methodology is best understood in comparison with standard practice in the VAR literature.
VAR analysis involves three steps: (1) fit a linear model to data on variables of interest, such as output, interest rates, and prices and generate a set of reduced form errors; (2) identify the structural disturbances to the variables from the reduced form errors; and (3) use the estimated model to analyze the effect that these disturbances have on the endogenous variables. This last step implicitly involves regressing the reduced form errors at various horizons on the structural disturbances. The main role played by the VAR in this analysis is to generate the forecasts that give rise to the reduced form errors employed in steps (1) and (3). I use market expectations in the place of VAR forecasts at these points.
There are several advantages to my methodology. First, private forecasts provide the conditional expectation of output and inflation, whereas the VAR provides only the best linear forecast based on the variables included in the system. For this reason, private forecasts are more likely than VAR’s to be robust to changes in the policy regime and to non-linearities in the economy. Second, by using private expectations data I am implicitly using the information set employed by the private agents.! This implies that I can control for private in- formation in a more direct and precise manner.
The VAR information set, however, only includes the variables that are included in the model. A related criticism of the VAR is the basis on which the included variables are chosen. VAR researchers seem to be satisfied that they have identified a monetary shock when the effect of money on output and prices matches their view of what a money shock should look like. Cochrane (1994) states that, “.
empirical researchers typically fish for VAR specifications to produce impulse-responses that capture qualitative monetary dy- namics, for example as described in Friedman (1968). For example, Christiano, Eichenbaum and Evans (1996) state that “. The reason that we include a measure of commodity prices in our analysis is to avoid the well-known ‘price puzzle’ .”, and 1As Cochrane (1994) points out “. Shock identification procedures are sensitive to the fact that economic agents and policy makers base their forecasts on more variables than we include in our VARs.
Sims and Zha (1998) state that “. With this identification, money supply shocks .
