This dissertation examines the process by which buyers encode and store price information in their memories and how the information is retrieved when such a need arises. Using theories in human learning and memory, it has been argued that buyers’ learning of price information is primarily influenced by their learning plans and the criteria they use pin choice decisions. Because of the differences in learning and choice task orientations, buyers are postulated to encode and store the information differently and therefore, different memory tests are necessary to investigate the retrieval mechanisms and thereby making inferences about their knowledge of price. While it is recognized that buyers may encode and retrieve price information in many different ways, this research has examined the differential impact of learning and choice task orientations on their recall, recognition, and ranking performances. The hypotheses developed in this research were tested in a laboratory experiment using ninety women shoppers as subjects. The two levels of learning (incidental and intentional) and the three levels of choice task orientations (non-price, mixed, and price) were fully crossed in a 2 x 3 full-factorial between-subjects design. Subjects, after being randomly assigned to one of the six experimental conditions took part in a simulated grocery shopping. Having made their selections, subjects responded to recall, recognition, and ranking memory tests involving prices of the items selected. Subjects also indicated their confidence about the accuracy of their responses. The accuracy and confidence ratings were used as dependent measures when testing the hypotheses. Since accuracy measures were dichotomous (correct or incorrect) in nature, loglinear modes were tested using maximum likelihood estimation procedure. For continuous dependent measure (e.g. confidence), ordinary least square estimations were carried out in a univariate ANOVA framework. In addition, several multiple comparison procedures were used to test differences between mean accuracy and confidence scores. The data analysis supported fifteen out of sixteen hypothesized relationships. The results supported the argument that buyers’ learning of price information improves with greater use of price in their choice decisions and with greater need to remember the information for later use. Overall, recognition was found to be a more appropriate retrieval mechanism than recall. Need for remembering specific prices did not significantly improve buyers° ability to rank items in terms of their expensiveness. The conceptualization and the research results are expected to make both theoretical and methodological contributions in pricing research. Particularly, the issues involving formation of reference prices and the manner in which the internal reference prices are retrieved and used in iii choice decisions are partially addressed using a consumer information processing perspective. Nonetheless, future research is needed to resolve additional issues in price perception research. / Ph. D.

This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.

This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.

Thesis (Ph.D.)--McMaster University, 2006. / Supervisor: Thomas Crossley. Includes bibliographical references.

Thesis (M.Sc. (Agricultural Economics)) -- University of Limpopo, 2022 / Agricultural production measures the performance and efficiency of a country’s agricultural sector. The state of agricultural production can be assessed through the value of agricultural production, which is a product of agricultural gross production and output prices in monetary terms. The study examines the relationship between the value of agricultural production, government spending on agriculture, and other selected variables. Annual data for the value of agricultural production, government expenditure in agriculture, consumer price index, average annual rainfall, food import value, and population from 1983 to 2019 were collected from different sources and were used in the analysis for this study. The Johansen cointegration test was used to determine the existence of a long-run relationship between the value of agricultural production and selected variables by using both the trace and eigenvalue tests. The results indicated that there is a long run relationship among the variables. The study further used the Granger causality test to check the causality between the value of agricultural production and government expenditure in agriculture. The results show that there is no causal effect between the two variables. Lastly, the study used a Vector autoregressive (VAR) model to determine the relationship between the value of agricultural production and selected variables. The results of the VAR model indicated that government expenditure on agriculture, average annual rainfall, food import value, and population positively affect the value of agricultural production. The study also found that the consumer price index negatively affects the value of agricultural production. The study recommends that the government increase its spending on the agricultural sector, which could be in the form of research investment in technologies such as climate-smart agricultural technologies. Additionally, the study recommends that policymakers should review the monetary policy of South Africa to ensure price stability and prevent inflation. Lastly, the study recommends that the South African government should discourage imports and encourage South African agricultural producers to produce more major imported food products.

Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2022 / Using the ARFIMA (autoregressive and fractionally integrated moving aver age) model extended with sGARCH (standard generalised autoregressive con ditional heteroscedasticity) and ’gjrGARCH (Glosten-Jagannathan-Runkle gen eralised autoregressive conditional heteroscedascity) innovations, fractional in tegration approach and state space model, this study has empirically examined persistency of inflation dynamics of Ghana and South Africa, the only two coun tries in Sub-Saharan Africa with Inflation Targeting (IT) monetary policy. The first part of the analysis employed monthly CPI (Consumer Price Index) in flation series for the period January 1971 to October 2014 obtained from the Bank of Ghana (BoG), and for the period January 1995 to December 2014 ob tained from Statistics South Africa. The second part involves the estimation of threshold effect of inflation on economic growth using annual data obtained from the IMF (International Monetary Fund) database for the period 1981 to 2014, for both countries. Results from the study showed that structural breaks, long memory and non linearities (or regime shifts) are largely responsible for inflation persistence, hence the ever-changing nature of inflation rates of Ghana and South Africa. ARFIMA(3,0.35,1)-‘gjrGARCH(1,1) under Generalised Error Distribution (GED) and ARFIMA(3,0.50,1)-‘gjrGARCH(1,1) under Student-t Distribution (STD) mod els provided the best fit for persistence in the conditional mean (or level) of CPI for Ghana and South Africa, respectively. The results from these models pro vided evidence of time-varying conditional mean and volatility in CPI inflation rates of both countries. The two models also revealed an asymmetric effect of inflationary shocks, where negative shocks appear to have greater impact than positive shocks, in terms of persistence on the conditional mean with time varying volatility. This thesis proposes a model that combines fractional integration with non linear deterministic terms based on the Chebyshev polynomials in time for the analysis of CPI inflation rates of Ghana and South Africa. We tested for non-linear deterministic terms in the context of fractional integration and esti mated the fractional differencing parameters, d to be 1.11 and 1.32 respectively, for the Ghanaian and the South African inflation rates, but the non-linear trends were found to be statistically insignificant in the two series. New ev idence from this thesis depicts that inflation rate of Ghana is highly persistent and non-mean reverting, with an estimated fractional differencing parameter, d > 1.0, and will therefore require some policy action to steer inflation back to stability. However, the South African inflation series was found to be a cyclical process with an order of integration estimated to be d = 0.7, depicting mean reversion, with the length of the cycles approximated to last for 80 months. Finally, the thesis incorporated structural breaks, long memory, non-linearity, and some explanatory variables into a state space model and estimated the threshold effect of inflation on economic growth. The empirical results suggest that inflation below the estimated levels of 9% and 6% for Ghana and South Africa respectively, will be conducive for economic growth. The policy implications of these results for both countries are as follows. First, both series had similar properties responsible for inducing inflation persistence such as structural breaks, non-linearities, long memory and asymmetric re sponse to negatives shocks - but with varied degrees of magnitude. For both countries, the conditional mean and unobserved components such as volatility for both countries were found to be time-varying. This thesis, therefore, recom mends to the BoG and the South African Reserve Bank (SARB) - responsible for monetary policies, and the Finance Ministers of both governments - respon sible for fiscal policies, to take the above-mentioned properties into account in the formulation of their monetary policies. Second, the thesis recommends that the BoG and the SARB consolidate the IT policy, since keeping inflation below the targets set of 9% and 6%, respectively for Ghana and South Africa, will boost economic growth. Third, policymakers could also design measures (monetary and fiscal policies) such as increase in interest rates, credit control, and reduction of unnecessary expenditure, among others, to control inflation due to its adverse effects on market volatility. Even though an increase in interest rates could assist in curtailing the recent and anticipated increase in inflation rates in both countries, where targets have been missed by Ghana and South Africa, it will also be prudent to legislate monetary policies around demand-supply side since the problem of both coun tries appears to be more of a structuralist than a monetarist. It is, therefore, recommended that both countries tighten the IT monetary policy in order to re duce inflation persistence. This will eventually impact on poverty and income distribution with ramifications for economic growth and/or development. The fourth implication of these results is that governments and central banks should be mindful of the actions and decisions they take, in the sense that unguarded decisions and unnecessary alarms could raise uncertainties in the economy, which could, in turn, affect the future trajectory of inflation. Finally, the thesis recommends that governments of both countries strengthen the pri vate sector, which is the engine of growth. For small and open economies such as Ghana and South Africa, this will grow the economy through job creation and restore investor confidence. / National Research Foundation (NRF), Department of Science and Technology (DST), Telkom’s Tertiary Education Support Programme (TESP) and the NRF-DST Centre of Excellence for Mathematical and Statistical Sciences (CoE-MaSS)

Thesis (M.Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2022 / Beef and chicken meat play a very crucial role in providing food to South African consumers. However, the rise of food prices in South Africa is viewed to curtail progress and drives consumers into debt and forgone opportunity to access food. Hence, it is of importance to understand the consumer price index (CPI) of meat and the disaggregate components of beef and chicken meat producer price indexes (PPI) as they give a clear insight into how individual commodities contribute to the general and food price inflation. The study aimed to comparatively analyse the relationship between PPI beef and CPI meat as well as PPI chicken meat and CPI meat in South Africa from 1991 to 2018. The objectives of the study were to compare the indexes’ variability, correlation, and causality between the different PPI and CPI components. The objectives were analysed using the Coefficient of variation (CV), the Pearson coefficient correlation, the Granger causality test, and the Vector Error Correction model. The CV findings highlight that PPI beef had high variability (65%) compared to CPI meat (56.7%), whereas PPI chicken meat had low variability (49.2%) compared to CPI meat(56.7%). There was evidence of a positive correlation (0.99) between PPI beef and CPI meat as well as PPI chicken meat and CPI meat using Pearson coefficient correlation. In addition, a long-run relationship was found between PPI beef and CPI meat as well as between PPI chicken meat and CPI meat by using the VEC model. Granger causality results indicated that there was a unidirectional relationship from PPI chicken meat to CPI meat, and independent relationships were found from PPI beef to CPI meat, CPI meat to PPI beef as well as CPI meat to PPI chicken meat. Based on the findings, the study recommends that policymakers, through evaluation of monetary policies, should continue maintaining a specific inflation target range as that will assist in stabilising meat prices in the economy. At the same time, protect meat producers against input price inflation using instruments such as input subsidies, grants, and the provision of modern technologies. / National Research Foundation (NRF)