Academic literature on the topic 'Inflation (Finance) Australia Econometric models'

This paper assesses the presence and importance of the neo-Fisher effect in postwar data. It formulates and estimates an empirical and a New Keynesian model driven by stationary and nonstationary monetary and real shocks. In accordance with conventional wisdom, temporary increases in the nominal interest rate are estimated to cause decreases in inflation and output. The main finding of the paper is that permanent monetary shocks that increase the nominal interest rate and inflation in the long run cause increases in interest rates, inflation, and output in the short run and explain about 45 percent of inflation changes. (JEL E12, E23, E31, E43, E52)

AbstractOil price showed sharp fluctuations in recent years which revived the interest in its effect on inflation. In this paper, we discuss the relationship between oil price and inflation in Spain, at national and regional levels, and making the distinction between energy and non-energy inflation. To this end, we fit econometric models to measure the effect of oil price shocks on inflation and to predict them under different scenarios. Our results show that almost half of the volatility of changes in total inflation is explained by changes in oil price. As could be expected, the energy component of inflation drives this effect. We also find that, under the most likely scenarios, 1-year ahead total inflation will be moderate, with relevant differences across regions.

The paper estimates the trajectory of trend inflation for Russia. A discussion of inflation measures used in macroeconomic models is presented, as well as the analysis of theoretical and empirical models that include a trend inflation indicator for monetary policy analysis. The paper also provides an overview of the use of trend inflation by monetary authorities of developed countries and emerging markets. Based on the methodology for assessing trend inflation with the help of models of unobservable components, the Kalman filter and including structural factors, the trajectory of trend inflation for the Russian economy from the beginning of 2001 to the end of 2021 is obtained. In addition, the paper provides a historical decomposition of cyclical inflation into structural shocks, as well as the decomposition of the variance of its forecast error into the considered shocks for 24 months in advance. The results of the econometric analysis testify in favor of a gradual decrease in the trend inflation rate to 4% per year after the 2015 crisis and further stabilization at this level. The situation in 2022 can be analyzed by analogy with the period of 2014—2015, one can expect a similar scenario for trend and actual inflation to return to pre-crisis levels in 2022 within one year (by March 2023).

Abstract Econometric modeling and exponential smoothing techniques are two quantitative forecasting methods with good results in practice, but the objective of the research was to find out which of the two techniques are better for short run predictions. Therefore, for inflation, unemployment and interest rate in the Czech Republic various accuracy indicators were calculated for the predictions based on these methods. Short run forecasts on a horizon of 3 months were made for December 2011-February 2012, the econometric models being updated. For the Czech Republic, the exponential smoothing techniques provided more accurate forecasts than the econometric models (VAR(2) models, ARMA procedure and models with lagged variables). One explication for the better performance of smoothing techniques would be that in the chosen countries the short run predictions were more influenced by the recent evolution of the indicators.

Purpose This study aims to address the issue of prediction of inflation differences for an economy that considers either fixing its exchange rate or joining a currency union. In this setting, individual countries have limited control over their inflation, and anticipating the possible course of domestic inflation relative to inflation abroad becomes an important input in policy-making. In this context, the author compares simple forecast heuristics and econometric modeling. Design/methodology/approach The study compares two basically different approaches. The first approach of forecasting consists of simple heuristics. Various heuristics are considered that differ with respect to the economic reasoning that goes into quantifying the forecast rules. The simplest such forecasting heuristic suggests that the average over all available observations of inflation differentials should be taken as a predictor for the future. Bringing more economic insight to bear suggests a further heuristic according to which historical inflation differentials should be adjusted for changes in the nominal exchange rate. A further variant of this approach suggests that a forecast should exclusively rely on data from earlier times under a pegged exchange rate. A fundamentally different approach to prediction builds on dynamic econometric models estimated by using all available historical data independent of the currency regime. Findings The author studies three small member countries of the Eurozone, i.e. Finland, Luxembourg and Portugal. For the evaluation of the various forecasting strategies, he performs out-of-sample predictions over a horizon of five years. The comparison of the four different forecasting strategies documents that the variant of the forecast heuristic that draws on data from earlier experiences under fixed exchange rates performs better than the forecast based on the estimated econometric model. Practical implications The findings of this study provide helpful guidelines for countries considering either joining a currency union or fixing their exchange rate. The author shows that a simple forecasting heuristic gives sound advice for assessing the likely course of inflation. Originality/value This study describes how economic theory can guide the selection of historical data for assessing likely future developments. The analysis shows that using a simple heuristic based on historical analogy can lead to better forecasts than the analytically more sophisticated approach of econometric modeling.

The debt neutrality hypothesis which has been a source of major controversies in the theory of public finance, and macroeconomics has at the same time generated a vast literature on the implications of budgetary deficits and public debt on various subsectors/ variables of the economy, such as inflation, interest rates, current account deficit, etc. Tax discounting has been one of the fields of research associated with debt neutrality. The econometric estimation of some of the standard models of taxdiscounting has shown that consumer response to fiscal policy in Pakistan reflects neither the extreme Barro-like rational anticipation of future tax liabilities nor the Buchanan-type extreme fiscal myopia. It broadly follows a middle path between these extremes. The controversy relating to debt neutrality is quite old in economic theory. However, due to its serious and far-reaching implications for the formulation of fiscal policy and macroeconomic management, the issues of debt neutrality have assumed a foremost position in economic theoretisation and empirical testing. This controversy is based on two important questions: (a) Who bears the burden of the debt? (b) Should debt be used to finance public expenditure? The first question centres on whether the debt can be shifted forward in time, while the second question explores whether taxation is equivalent to debt in its effects on the national economy.

Count data, including zero counts arise in a wide variety of application, hence models for counts have become widely popular in many fields. In the statistics field, one may define the count data as that type of observation which takes only the non-negative integers value. Sometimes researchers may Counts more zeros than the expected. Excess zero can be defined as Zero-Inflation. Data with abundant zeros are especially popular in health, marketing, finance, econometric, ecology, statistics quality control, geographical, and environmental fields when counting the occurrence of certain behavioral and natural events, such as frequency of alcohol use, take drugs, number of cigarettes smoked, the occurrence of earthquakes, rainfall, and etc. Some models have been used to analyzing count data such as the zero-inflated Poisson (ZIP) model and the negative binomial model. In this paper, the models, Poisson, Negative Binomial, ZIP, and ZINB were been used to analyze rainfall data.

This study aims at investigating the impact of Covid-19 pandemic and Global Financial Crisis (GFC) on the performance of selected listed firms in Jordan. To achieve this objective, the study uses panel data for twenty firms over the period 2001-2020, obtained from Amman Stock Exchange database. All the study variables were found to be stationary at level, therefore, fixed and random effect models were applied to estimate two econometric equations with two performance indices. The results have revealed that both inflation and GFC have insignificant effect on the profitability of these firms, while debt ratio has a significant negative impact on their performance. The outcomes have also demonstrated the significant negative impact of Covid-19 pandemic on the profitability of such firms. Based on these results, the study has introduced some recommendations that may help in mitigating the adverse consequences of Covid-19 pandemic and in improving the profitability of Jordanian firms.

Purpose The purpose of this paper is to estimate the Tanzanian shadow economy (SE) from 2003 to 2015 and test the statistical relationships between the SE and its potential causes and indicators. Design/methodology/approach The econometric analysis is based on a multiple indicators multiple causes (MIMIC) model. To calibrate the SE from the estimates, the authors adopt the value of 55.4 percentage of the SE to official GDP from the literature for the base year 2005. Findings The SE ranges from 52 to 61 per cent of official GDP and slightly decreases from 2013 to 2015. Increase in inflation, unemployment and government spending were the main drivers of the SE dynamics. Research limitations/implications Given the challenges facing estimation of the SE (e.g. small sample size, exogenous estimate to calibrate the model, meaning of the latent variable), quantification of SE should be considered to be rough measures. Practical implications To lower the size of the SE, the government needs to keep inflation and unemployment stable over time, to reduce government spending because it creates pressure on tax collection due to the limited tax base. Originality/value This is the first study specifically focused on Tanzanian SE based on the MIMIC approach. Existing estimates of Tanzanian SE are calculated by monetary models or apply a common MIMIC specification to the worldwide context.

The aim of this paper is to evaluate the importance of housing price. We compare the evolution of three different types of housing prices (list, sale and appraisal prices). The objective is to see the marketing and financial consequences of using each type of housing price. To do this, a dataset of a real estate company and its financial intermediary with all of these types of housing prices is used. We estimate econometric models in which the dependent variables are: price (appraisal, selling or list), mark-up, loan to value and foreclosures. The results show evidence of the consequences of using a specific housing price in terms of inflation calculation, financial assets, and collateral valuation and mortgage default, among others.

[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.

This thesis is a technical inquiry into remedies for high inflation. In its center there is the usual tradeoff between inflation aversion on the one hand and some benefit from inflation via Phillips curve effects on the other hand. Most remarkable and pioneering work for us is the famous Barro-Gordon model - see (Barro & Gordon 1983a) respectively (Barro & Gordon 1983b). Parts of this model form the basis of our work here. Though being well known the discretionary equilibrium is suboptimal the question arises how to overcome this. We will introduce four different models, each of them giving a different perspective and way of thinking. Each model shows a (sometimes slightly) different way a central banker might deliver lower inflation than the one shot Barro-Gordon game at a first glance would suggest. To cut a long story short we provide a number of reasons for believing that the purely discretionary equilibrium may be rarely observed in real life. Further the thesis provides new insights for derivative pricing theories. In particular, the potential role of financial markets and instruments will be a major focus. We investigate how such instruments can be used for monetary policy. On the contrary these financial securities have strong influence on the behavior of the central bank. Taking this into account in chapters 3 and 4 we come up with a new method of pricing inflation linked derivatives. The latter to the best of our knowledge has never been done before - (Persson, Persson & Svenson 2006), as one of very view economic works taking into account financial markets, is purely focused on the social planer's problem. A purely game theoretic approach is done in chapter 2 to change the original Barro-Gordon. Here we deviate from a purely rational and purely one period wise thinking. Finally in chapter 5 we model an asymmetric information situation where the central banker faces a trade off between his current objective on the one hand and benefit arising from not perfectly informed agents on the other hand. In that sense the central bank is also concerned about its reputation.

This study deals with the estimation of the optimal hedge ratios using various econometric models. Most of the recent papers have demonstrated that the conventional ordinary least squares (OLS) method of estimating constant hedge ratios is inappropriate, other more complicated models however seem to produce no more efficient hedge ratios. Using daily AOIs and SPI futures on the Australian market, optimal hedge ratios are calculated from four different models: the OLS regression model, the bivariate vector autoaggressive model (BVAR), the error-correction model (ECM) and the multivariate diagonal Vcc GARCH Model. The performance of each hedge ratio is then compared. The hedging effectiveness is measured in terms of ex-post and ex-ante risk-return traHe-off at various forcasting horizons. It is generally found that the GARCH time varying hedge ratios provide the greatest portfolio risk reduction, particularly for longer hedging horizons, but hey so not generate the highest portfolio return.

This research questions whether technical trading rules can help predict stock price movements for a sample of stocks selected from four equity markets from the Asia-Pacific region: Australia, Malaysia, Hong Kong and Thailand for the period 1989-2008. The research is split into two stages. Stage-1 of the research tests the predictability of technical trading rules against a buyand- hold strategy. The variable moving average (VMA), fixed moving average (FMA) and the trading range break (TRB) trading rules are applied to this research. Economic predictability of these rules is examined by comparing returns conditional on a trading rule buy (sell) signal against an unconditional buy-and-hold return. Any existence of excess returns can thus be established. This follows with a statistical analysis of returns using a traditional t-test methodology. Traditional statistical tests assume normally distributed returns with independent observations and a non-changing distribution across time. In Stage-2 of this research a bootstrap checks whether features such as non-normality, time-varying moments and serial correlation bias test statistics. The bootstrap involves assumptions regarding the underlying returns generating process (RGP) and allows returns conditional on a trading rule buy (sell) signal from the original stock price series to be compared with conditional returns simulated from four common null models: RW, AR (1), GARCH-M and E-GARCH models. Simulated p-values are calculated in conjunction with simulated distributions and are applied in lieu of the theoretical normal distribution. Given this process it is possible to infer as to whether non-linear dependencies in returns can be captured by any of the three trading rules. Given the null model output standard t-test outcomes of predictability of technical trading rules may be diminished and/or eliminated. Conclusions are drawn as to the predictability and profitability of the VMA, FMA and TRB trading rules when applied to the chosen stock samples. Findings of this research indicate returns conditional on technical trading rules exceed unconditional buy-and-hold returns for all stocks. Thai sample output indicates strong support in favour of the predictability of standard test results supporting the use of technical trading rules. Output for Australia, Hong Kong and Malaysia indicates that previous standard t-test outcomes of predictability may be diminished and/or eliminated. This implies that the underlying RGP may be characterised by underlying features of some/all of the stochastic models.

This thesis addresses three relevant macroeconomic issues: (i) why

Central Banks behave so cautiously compared to optimal theoretical

benchmarks, (ii) do monetary variables add information about

future Euro Area inflation to a large amount of non monetary

variables and (iii) why national saving and investment are so

correlated in OECD countries in spite of the high degree of

integration of international financial markets.

The process of innovation in the elaboration of economic theory

and statistical analysis of the data witnessed in the last thirty

years has greatly enriched the toolbox available to

macroeconomists. Two aspects of such a process are particularly

noteworthy for addressing the issues in this thesis: the

development of macroeconomic dynamic stochastic general

equilibrium models (see Woodford, 1999b for an historical

perspective) and of techniques that enable to handle large data

sets in a parsimonious and flexible manner (see Reichlin, 2002 for

an historical perspective).

Dynamic stochastic general equilibrium models (DSGE) provide the

appropriate tools to evaluate the macroeconomic consequences of

policy changes. These models, by exploiting modern intertemporal

general equilibrium theory, aggregate the optimal responses of

individual as consumers and firms in order to identify the

aggregate shocks and their propagation mechanisms by the

restrictions imposed by optimizing individual behavior. Such a

modelling strategy, uncovering economic relationships invariant to

a change in policy regimes, provides a framework to analyze the

effects of economic policy that is robust to the Lucas'critique

(see Lucas, 1976). The early attempts of explaining business

cycles by starting from microeconomic behavior suggested that

economic policy should play no role since business cycles

reflected the efficient response of economic agents to exogenous

sources of fluctuations (see the seminal paper by Kydland and Prescott, 1982}

and, more recently, King and Rebelo, 1999). This view was challenged by

several empirical studies showing that the adjustment mechanisms

of variables at the heart of macroeconomic propagation mechanisms

like prices and wages are not well represented by efficient

responses of individual agents in frictionless economies (see, for

example, Kashyap, 1999; Cecchetti, 1986; Bils and Klenow, 2004 and Dhyne et al. 2004). Hence, macroeconomic models currently incorporate

some sources of nominal and real rigidities in the DSGE framework

and allow the study of the optimal policy reactions to inefficient

fluctuations stemming from frictions in macroeconomic propagation

mechanisms.

Against this background, the first chapter of this thesis sets up

a DSGE model in order to analyze optimal monetary policy in an

economy with sectorial heterogeneity in the frequency of price

adjustments. Price setters are divided in two groups: those

subject to Calvo type nominal rigidities and those able to change

their prices at each period. Sectorial heterogeneity in price

setting behavior is a relevant feature in real economies (see, for

example, Bils and Klenow, 2004 for the US and Dhyne, 2004 for the Euro

Area). Hence, neglecting it would lead to an understatement of the

heterogeneity in the transmission mechanisms of economy wide

shocks. In this framework, Aoki (2001) shows that a Central

Bank maximizing social welfare should stabilize only inflation in

the sector where prices are sticky (hereafter, core inflation).

Since complete stabilization is the only true objective of the

policymaker in Aoki (2001) and, hence, is not only desirable

but also implementable, the equilibrium real interest rate in the

economy is equal to the natural interest rate irrespective of the

degree of heterogeneity that is assumed. This would lead to

conclude that stabilizing core inflation rather than overall

inflation does not imply any observable difference in the

aggressiveness of the policy behavior. While maintaining the

assumption of sectorial heterogeneity in the frequency of price

adjustments, this chapter adds non negligible transaction

frictions to the model economy in Aoki (2001). As a

consequence, the social welfare maximizing monetary policymaker

faces a trade-off among the stabilization of core inflation,

economy wide output gap and the nominal interest rate. This

feature reflects the trade-offs between conflicting objectives

faced by actual policymakers. The chapter shows that the existence

of this trade-off makes the aggressiveness of the monetary policy

reaction dependent on the degree of sectorial heterogeneity in the

economy. In particular, in presence of sectorial heterogeneity in

price adjustments, Central Banks are much more likely to behave

less aggressively than in an economy where all firms face nominal

rigidities. Hence, the chapter concludes that the excessive

caution in the conduct of monetary policy shown by actual Central

Banks (see, for example, Rudebusch and Svennsson, 1999 and Sack, 2000) might not

represent a sub-optimal behavior but, on the contrary, might be

the optimal monetary policy response in presence of a relevant

sectorial dispersion in the frequency of price adjustments.

DSGE models are proving useful also in empirical applications and

recently efforts have been made to incorporate large amounts of

information in their framework (see Boivin and Giannoni, 2006). However, the

typical DSGE model still relies on a handful of variables. Partly,

this reflects the fact that, increasing the number of variables,

the specification of a plausible set of theoretical restrictions

identifying aggregate shocks and their propagation mechanisms

becomes cumbersome. On the other hand, several questions in

macroeconomics require the study of a large amount of variables.

Among others, two examples related to the second and third chapter

of this thesis can help to understand why. First, policymakers

analyze a large quantity of information to assess the current and

future stance of their economies and, because of model

uncertainty, do not rely on a single modelling framework.

Consequently, macroeconomic policy can be better understood if the

econometrician relies on large set of variables without imposing

too much a priori structure on the relationships governing their

evolution (see, for example, Giannone et al. 2004 and Bernanke et al. 2005).

Moreover, the process of integration of good and financial markets

implies that the source of aggregate shocks is increasingly global

requiring, in turn, the study of their propagation through cross

country links (see, among others, Forni and Reichlin, 2001 and Kose et al. 2003). A

priori, country specific behavior cannot be ruled out and many of

the homogeneity assumptions that are typically embodied in open

macroeconomic models for keeping them tractable are rejected by

the data. Summing up, in order to deal with such issues, we need

modelling frameworks able to treat a large amount of variables in

a flexible manner, i.e. without pre-committing on too many

a-priori restrictions more likely to be rejected by the data. The

large extent of comovement among wide cross sections of economic

variables suggests the existence of few common sources of

fluctuations (Forni et al. 2000 and Stock and Watson, 2002) around which

individual variables may display specific features: a shock to the

world price of oil, for example, hits oil exporters and importers

with different sign and intensity or global technological advances

can affect some countries before others (Giannone and Reichlin, 2004). Factor

models mainly rely on the identification assumption that the

dynamics of each variable can be decomposed into two orthogonal

components - common and idiosyncratic - and provide a parsimonious

tool allowing the analysis of the aggregate shocks and their

propagation mechanisms in a large cross section of variables. In

fact, while the idiosyncratic components are poorly

cross-sectionally correlated, driven by shocks specific of a

variable or a group of variables or measurement error, the common

components capture the bulk of cross-sectional correlation, and

are driven by few shocks that affect, through variable specific

factor loadings, all items in a panel of economic time series.

Focusing on the latter components allows useful insights on the

identity and propagation mechanisms of aggregate shocks underlying

a large amount of variables. The second and third chapter of this

thesis exploit this idea.

The second chapter deals with the issue whether monetary variables

help to forecast inflation in the Euro Area harmonized index of

consumer prices (HICP). Policymakers form their views on the

economic outlook by drawing on large amounts of potentially

relevant information. Indeed, the monetary policy strategy of the

European Central Bank acknowledges that many variables and models

can be informative about future Euro Area inflation. A peculiarity

of such strategy is that it assigns to monetary information the

role of providing insights for the medium - long term evolution of

prices while a wide range of alternative non monetary variables

and models are employed in order to form a view on the short term

and to cross-check the inference based on monetary information.

However, both the academic literature and the practice of the

leading Central Banks other than the ECB do not assign such a

special role to monetary variables (see Gali et al. 2004 and

references therein). Hence, the debate whether money really

provides relevant information for the inflation outlook in the

Euro Area is still open. Specifically, this chapter addresses the

issue whether money provides useful information about future

inflation beyond what contained in a large amount of non monetary

variables. It shows that a few aggregates of the data explain a

large amount of the fluctuations in a large cross section of Euro

Area variables. This allows to postulate a factor structure for

the large panel of variables at hand and to aggregate it in few

synthetic indexes that still retain the salient features of the

large cross section. The database is split in two big blocks of

variables: non monetary (baseline) and monetary variables. Results

show that baseline variables provide a satisfactory predictive

performance improving on the best univariate benchmarks in the

period 1997 - 2005 at all horizons between 6 and 36 months.

Remarkably, monetary variables provide a sensible improvement on

the performance of baseline variables at horizons above two years.

However, the analysis of the evolution of the forecast errors

reveals that most of the gains obtained relative to univariate

benchmarks of non forecastability with baseline and monetary

variables are realized in the first part of the prediction sample

up to the end of 2002, which casts doubts on the current

forecastability of inflation in the Euro Area.

The third chapter is based on a joint work with Domenico Giannone

and gives empirical foundation to the general equilibrium

explanation of the Feldstein - Horioka puzzle. Feldstein and Horioka (1980) found

that domestic saving and investment in OECD countries strongly

comove, contrary to the idea that high capital mobility should

allow countries to seek the highest returns in global financial

markets and, hence, imply a correlation among national saving and

investment closer to zero than one. Moreover, capital mobility has

strongly increased since the publication of Feldstein - Horioka's

seminal paper while the association between saving and investment

does not seem to comparably decrease. Through general equilibrium

mechanisms, the presence of global shocks might rationalize the

correlation between saving and investment. In fact, global shocks,

affecting all countries, tend to create imbalance on global

capital markets causing offsetting movements in the global

interest rate and can generate the observed correlation across

national saving and investment rates. However, previous empirical

studies (see Ventura, 2003) that have controlled for the effects

of global shocks in the context of saving-investment regressions

failed to give empirical foundation to this explanation. We show

that previous studies have neglected the fact that global shocks

may propagate heterogeneously across countries, failing to

properly isolate components of saving and investment that are

affected by non pervasive shocks. We propose a novel factor

augmented panel regression methodology that allows to isolate

idiosyncratic sources of fluctuations under the assumption of

heterogenous transmission mechanisms of global shocks. Remarkably,

by applying our methodology, the association between domestic

saving and investment decreases considerably over time,

consistently with the observed increase in international capital

mobility. In particular, in the last 25 years the correlation

between saving and investment disappears.

Doctorat en sciences économiques, Orientation économie
info:eu-repo/semantics/nonPublished

In 1993, Kenya liberalised its trade policy and allowed the Kenyan Shillings to freely float. This openness has left Kenya's domestic prices vulnerable to the effects of exchange rate fluctuations. One of the objectives of the Central Bank of Kenya is to maintain inflation levels at sustainable levels. Thus it has become necessary to determine the influence that exchange rate changes have on domestic prices given that one of the major determinants of inflation is exchange rate movements. For this reason, this thesis examines the magnitude and speed of exchange rate pass-through (ERPT) to domestic prices in Kenya. In addition, it takes into account the direction and size of changes in the exchange rates to determine whether the exchange rate fluctuations are symmetric or asymmetric. The thesis uses quarterly data ranging from 1993:Ql - 2008:Q4 as it takes into account the period when the process of liberalization occurred. The empirical estimation was done in two stages. The first stage was estimated using the Johansen (1991) and (1995) co integration techniques and a vector error correction model (VECM). The second stage entailed estimating the impulse response and variance decomposition functions as well as conducting block exogeneity Wald tests. In determining the asymmetric aspect of the analysis, the study followed Pollard and Coughlin (2004) and Webber (2000) frameworks in analysing asymmetry with respect to appreciation and depreciation and large and small changes in the exchange rate to import prices. The results obtained showed that ERPT to Kenya is incomplete but relatively low at about 36 percent in the long run. In terms of asymmetry, the results showed that ERPT is found to be higher in periods of appreciation than depreciation. This is in support of market share and binding quantity constraints theory. In relation to size changes, the results show that size changes have no significant impact on ERPT in Kenya.

The relevance of domestic and foreign capacity utilization rates in forecasting future inflation rate has been investigated empirically, using five industrialized countries for which the comparable data are available. It has been found that capacity utilization rates, both domestic and foreign, have a long run stable relationship with domestic inflation rate and a positive shock in the capacity utilization rate results in a significant, although a little bit delayed, acceleration in the domestic inflation rate. Various econometric techniques have been used and led to consistent empirical findings. The results in the present study, therefore, dispute the claim that an increase in capacity utilization rate may not necessarily lead to an accelerated inflation down the road.
Graduation date: 1995

Yuan, Jiang.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.
Includes bibliographical references (leaves 48-51).
Abstract also in Chinese.
Chapter Chapter 1 --- Introduction --- p.1
Chapter Chapter 2 --- Literature Review --- p.5
Chapter 2.1 --- Theoretical Literature --- p.5
Chapter 2.1.1 --- Menu Cost Model --- p.5
Chapter 2.1.2 --- Signal Extraction Model --- p.6
Chapter 2.1.3 --- Monetary Search Model --- p.7
Chapter 2.2 --- Empirical Literature --- p.8
Chapter Chapter 3 --- Inflation and Relative Price Variability in a Transitional Economy Evidence from China --- p.10
Chapter 3.1 --- Data and Variables --- p.10
Chapter 3.2 --- Inflation Decomposition --- p.19
Chapter 3.3 --- Empirical Evidence --- p.14
Chapter 3.3.1 --- Inflation and RPV --- p.14
Chapter 3.3.2 --- Robustness --- p.18
Chapter 3.4 --- Conclusion --- p.20
Chapter Chapter 4 --- Inflationary Regimes and Relative Prices --- p.22
Chapter 4.1 --- Introduction --- p.22
Chapter 4.2 --- The Change of Inflationary Regimes in China: 1978-2008 --- p.23
Chapter 4.3 --- Inflationary Regimes and Relative Price --- p.25
Chapter 4.3.1 --- Preliminary Evidence --- p.25
Chapter 4.3.2 --- Empirical Evidence --- p.27
Chapter 4.4 --- Structure Change --- p.32
Chapter 4.4.1 --- Endogenous Breakpoint Test --- p.32
Chapter 4.4.2 --- Test Results on the Changing Role of Expected Inflation --- p.33
Chapter 4.5 --- Conclusion --- p.35
Chapter Chapter 5 --- Institutional Cost and Relative Price Variability --- p.36
Chapter 5.1 --- Introduction --- p.36
Chapter 5.2 --- "Institutional Cost, Price Adjustment, and Relative Price Variability in China" --- p.38
Chapter 5.2.1 --- Background --- p.38
Chapter 5.2.2 --- Institutional cost --- p.39
Chapter 5.2.3 --- The relationship between institutional cost and relative price variability --- p.42
Chapter 5.3 --- The Empirical Evidence --- p.43
Chapter 5.4 --- Conclusion --- p.45
Chapter Chapter 6 --- Conclusion and Implications --- p.46
Reference --- p.48