Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 92-94).

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 97-102).

The general purpose of this study is to determine how South Africa’s early experience with the inflation targeting framework compares with the early experiences of Brazil, Chile, Israel, the Czech Republic and Poland. One developed economy, namely New Zealand, is included in the study since it was the pioneer of the inflation targeting framework. The experiences of these countries are compared along three dimensions: the stress tests the frameworks were subjected to and the monetary authorities’ responses to these tests; the adjustments made to the frameworks, operational and institutional procedures; and the credibility losses or gains as a result of these experiences. In order to arrive at a satisfactory conclusion to the problem a number of questions are explored. The theoretical basis of inflation targeting is analysed; the nature of South Africa’s framework is assessed to see how it conforms to general practices; South Africa’s early experience under the inflation targeting framework is assessed; and, lastly, South Africa’s experience is compared with the experiences of the six countries mentioned in the first paragraph. The assessment in this study shows that South Africa’s experience is not out of line when compared with other emerging-market countries. Many of the emerging markets surveyed faced significant stress tests and long-term obstacles that contributed to their failure to achieve their inflation targets in the early years of implementation. In response, the central banks surveyed sought to focus on the primary goal of monetary policy and to counter the second-round effects. As they became more experienced at operating an inflation targeting framework, some of the countries refined their frameworks. Ultimately, the survey draws lessons from the common experience of the seven countries assessed. It shows that credibility is key to the success of an inflation targeting framework, as is a supportive context. However, the survey also highlights that simply judging a country’s monetary policy success on whether it achieves its inflation targets is too limited an assessment for justifying the merit of an inflation targeting framework. / Prof. S. Chetty

The goal of this dissertation is to analyze issues that arise when policy makers try to learn about the economy while their policies are affecting it. The dissertation takes the form of three essays. The first essay examines how optimal policy affects equiUbrium economic outcomes in environments in which agents are both imperfectly informed about the state of the economy and able to learn by observing the actions of others. This type of environment, in which there is social learning, has received growing attention, but to date there has been little examination of strategic policy making in such settings. In particular, the question of whether policy, in the absence of a commitment technology, can be designed to increase the speed of information revelation remains open. The essay builds on a real options model of investment and shows how this framework can be extended to derive time consistent policies and the related equilibrium outcomes in social learning environments. By comparing the equilibrium induced by a policy maker to both the laissez-faire outcome and the social optimum, it is shown that the policy maker is able to achieve the second best outcome and reduce delay to the efficient level even in the absence of commitment. The second essay raises the question of whether the fact that policy makers play a dual role, as both information gatherers and economic managers, can explain the flattening of the Phillips Curve relationship between inflation and real activity that has been observed in both Canada and the U.S. over the 1990s. The paper models the central bank as both a provider of liquidity in a world where pre-set prices would otherwise cause potential gains from trade to go unrealized and a gatherer of information about real developments in the economy. The bank's information complements that of private agents so that, the central bank and private agents both wish to learn from the other. In equilibrium, this interaction gives rise to a Phillips curve relationship which both exhibits causality running from real activity to prices and justifies a feedback from prices to the setting of monetary instruments. The model implies that a decline in the slope of the Phillips curve may be a result of improvements in the manner in which central banks gather information about the economy. An investigation of the data for Canada and the U.S. finds support for the model. The third essay attempts a more thorough empirical investigation of the issues raised in the previous chapter. The paper enriches the dynamic aspects of the model to further examine its properties, but focuses mainly on attempting to uncover whether the types of changes to the Phillips curve relationship which had been previously documented in Canada and the U.S. have occurred in other OECD countries. The paper investigates this question using both single country and panel estimation and finds that the phenomenon of a declining slope in the Phillips curve relationship is prevalent in OECD countries throughout the 1980s and 1990s. Finally, the paper attempts to exploit the cross country data to provide more formal tests of the model's predictions regarding policy innovations and inflation targeting regimes. The results suggest that the model compares favourably to other potential explanations of the decline in the slope of the Phillips curve. / Arts, Faculty of / Vancouver School of Economics / Graduate

No description available.

No description available.

Inflation has been a recurrent and critical problem in many Latin American countries. Inflation is often combined with, among other problems, serious distortions in the structure of relative prices thus reducing efficiency of the pricing mechanism in allocating resources. The purpose of this study is to examine the effects of inflation and other variables on relative price variability in Peru using two different types of models. After preliminary evaluation of the stationarity properties of the series, a relative price variability measure is constructed using monthly data on 32 components of the CPI over the period 1979:12-1988:07. For the first models, series of expected and unexpected inflation in Peru, real exchange rate movements, and U.S. relative price variability are constructed and the effects of these variables on observed relative price variability are determined. The results indicate that increasing levels and unpredictability of inflation cause increased dispersion of relative prices. A distinction between expected and unexpected relative price changes is made in the second model. This distinction is relevant because not all price movements are viewed by agents as surprises that confuse price signals. To account for this distinction, a measure of conditional relative price variability is estimated using Engle's (1982) autoregressive conditional heteroskedasticity approach. Similarly, the conditional variance of domestic inflation is estimated and used as a measure of price uncertainty. Effects of the time-dependent conditional variances of domestic inflation and real exchange rate on a weighted average of the relative price shocks normalized by their conditional variances are evaluated and found statistically significant. Finally, both methods of testing empirically the hypothesis that inflation uncertainty increases relative price variability provided consistent results. / Master of Science

A multi-market model relating the variance of relative price changes to unanticipated inflation and real income was developed by Richard Parks for an article in the Journal of Political Economy. Parks used annual data in his estimation, and his use of the current rate of inflation as a predictor for next period's rate was rather simplistic. In this paper, his model was tested with two alternative specifications for anticipated inflation and with quarterly rather than annual data for the period 1947 through 1978. Anticipated inflation was estimated by (1) a time-series of past interest rates, and (2) a time-series of past inflation rates and the money supply. The multi-market model was estimated by employing the Cochrane-Orcutt iterative technique. The regression results gave additional support for Parks' model, but the respective roles for the two causal variables, unanticipated inflation, and real income, were reversed. Unanticipated inflation was seen to have a stronger effect in the quarterly data than it had in Parks' estimation with annual data. Relative price changes that result from an inflation that is unanticipated was said to be a temporary phenomenon. This was suggested to be the reason for the role reversal of the two causal variables because a temporary relationship such as the model attempts to estimate would be expected to show itself more significantly in quarterly data than it would in annual data. It was also suggested that unanticipated inflation may play a role in the persistence of staflation. / M.A.

M.Com. (Financial Economics) / Forecasting inflation is an important concern for economists and business alike throughout the world. Despite the relative success of macroeconomic forecasting models in forecasting inflation, there is potential to improve these models to account for nonlinear relationships between inflation and the chosen independent variables. Artificial neural networks (ANNs) have found increased applicability as a potential nonlinear forecasting tool that accounts for nonlinearity found in data. In this study, we investigate the ability of genetically optimised neural networks to forecast South African inflation. The results were compared to economic forecasts obtained from traditional econometric models as well as macroeconomic structural models. The results obtained show that the genetically optimised neural networks indicate some ability to be used as potential forecasting tools. Their biggest advantage over the traditional forecasting techniques is that they do not impose the restriction of linearity on the data to be forecasted.

by Chien Pak-hing, Leung Chi-lap. / Bibliography: leaves 192-195 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1982