A Comparison of Inflation Expectations and Inflation Credibility in South Africa : Results from Survey Data 1

This paper reports a comparison of South African household inflation expectations and inflation credibility surveys undertaken in 2006 and 2008. The objective is to test for possible feed-through between inflatin credibility and inflation expectations. It supplements similar earlier reserch that focused only on the 2006 survey results. The single most important difference between the survey results of 2006 and 2008 is that female and male respondents reported inflation expectations at the same level in 2006, while female respoondents expected higher inflation than male respondents in the 2008 inflation expecttions survey. More periodic survey data will be required for developing final ocnclusions on the possibility of feed-through effects. A very large percentage of respondents in the inflation credibility surveys indicate that they ’don’t know’ whether the historic rate of inflation is an accurte indication of price increases. It will be necessary to reconsider the structure of credibiity surveys to increase the number of respondents providing views on the accuracy of historic inflation data. JEL Classifications: E31, E52, E58


Introduction
An earlier paper (Rossouw et al., 2009) assessed South African inflation expectation and inflation credibility surveys undertaken among households in 2006 and tested a hypothesis that inflation expectations and inflation credibility do not vary between gender, population group, age and other characteristics.The main finding was that female respondents recorded a lower degree of acceptance of the credibility of historic inflation figures than male respondents, but that this difference did not feed into inflation expectations.This paper expands on earlier research in that it includes the results of additional sample years and expands on the characteristics explaining inflation expectations and inflation credibility by means of a logit framework and a multinomial model.This paper tests a hypothesis that sub-categories of households in the surveys exhibit the same linkages between inflation expectations and inflation credibility in 2006 and in 2008.Although preliminary conclusions can be drawn, additional surveys have to be undertaken over time before any time series conclusions will emerge.This paper summarises in Section 2 the literature on inflation expectations and inflation credibility among individual respondents in inflation-targeting countries.Section 3 highlights South African surveys of inflation expectations and inflation credibility among individual respondents.The surveys are compared and analysed in Section 4. The conclusions are contained in Section 5.

Summary of literature on inflation expectations and inflation credibility 1
This paper draws a distinction between inflation expectations and inflation credibility.Inflation expectations are used to describe and/or report views on the expected future trend and movement in price levels and, therefore, inflation.In this paper inflation credibility is used to describe and/or report views on past price-level movements and historic inflation, rather than to describe the credibility of monetary policy actions of central banks, as it is often used in literature (see Mishkin, 2004).
In addition, forward-looking inflation expectations in themselves are somewhat problematic, as these are sometimes also referred to as inflation forecasts.Other than in the minds of some economists, any distinction between inflation expectations and inflation forecasts is not immediately obvious.The former generally is regarded as subjective surveys of future inflation, while the latter is regarded as calculations of future inflation based on economic or econometric models (see for instance Collins English Dictionary, 2000, which describes expectation as anticipate and forecast as calculate).This paper attaches the same meaning to inflation expectations and inflation forecasts, as any possible differences are unimportant for this analysis.
Central banks in a cluster of twenty-four inflation-targeting countries aim at anchoring inflation expectations of economic subjects (businesses, consumers, employees, organised labour, etc) ( Powers (2005) observes that most inflation-targeting central banks use surveys to assess expectations of future inflation.It is somewhat surprising to find that available literature pays little attention to the approaches followed in inflation-targeting countries to obtain a measure of inflation expectations, given the considerable attention focused on the results of such expectations.While Fracasso et al. (2003) and the Bank of Iceland (2003) compared the monetary policy reports of twenty central banks in terms of clarity of assumptions, inflation forecasts, monetary policy decision-making process, quality of information and quantity of information, they did not assess the methodology used to obtain inflation forecasts or expectations.Likewise, ).The Swedish Riksbank surveys inflation perceptions of Swedish companies before each publication of its tri-annual Monetary Policy Report (Sveriges Riksbank, 2008).The credibility of historic Swedish inflation figures among individual respondents is surveyed by Growth from Knowledge, a market-research company (Palmqvist and Stromberg, 2004).Respondents in New Zealand and Sweden are requested to provide a numerical estimate of their perceptions of historic inflation figures.Of particular importance is a Swedish finding that " . . .with respect to the perceived rate . . .(of inflation) . . . the major difference . . .was found between men and women . . .(which) . . .apparently indicates that perceived rates are influenced by individual expenditure patterns" (Jonung, 1981: 968).
Representative inflation credibility surveys were undertaken independently in South Africa twice before, in 2006 and 2008 (see Rossouw, 2008;or Rossouw et al., 2009 for discussions of the first of these surveys).The international experience of differences in the credibility of inflation figures between male and female respondents was confirmed by the South African surveys (see for instance Rossouw, 2008;or Rossouw et al., 2009).These surveys are discussed and compared to South African inflation expectations surveys in the next section of this paper.
3 South African surveys of inflation expectations and inflation credibility among individual respondents The SA Reserve Bank (the Bank) uses the Bureau for Economic Research (BER) to conduct quarterly inflation expectation surveys among households on its behalf (Kershoff, 2000).3, Table 4 and Table 5.In both instances the large percentage of "don't know" responses are quite disconcerting, particularly when compared to the considerably lower percentage of similar responses in the inflation expectation surveys.It is also not possible to ascertain whether respondents answering "no" perceived higher or lower historic inflation.
4 Comparison and analysis of inflation expectation and inflation credibility surveys

Comparison of survey descriptions
The inflation expectation and inflation credibility surveys can be compared in terms of a number of salient features.The most obvious difference pertains to the statement and question raised with respondents.For the first period under review (the last quarter of 2006), respondents in the inflation expectations survey were asked to respond to "over the past five years prices increased by on average In 2006 the statement and question put to respondents in the inflation credibility survey was "South Africa's official rate of inflation (CPI) was 5,4 per cent in August 2006.Do you think this is a true reflection of average price increases?"(Markinor, 2006).In 2008 respondents had to respond to a statement and question that "South Africa's official rate of inflation (CPI) was 13,7 per cent in August 2008.Do you think this is a true reflection of average price increases?"(Ipsos- Markinor, 2008).
The most interesting finding in 2006 was in respect of gender.While a larger number and percentage of male respondents than female respondents accepted the credibility of historic inflation figures, a similar difference was not recorded with inflation expectations.Male and female respondents recorded the same inflation expectations in 2006.The inflation credibility survey conducted in 2008 again shows that female respondents attach lower credibility to historic inflation figures than male respondents.In this instance the lower credibility feeds into higher inflation expectations as is evidenced by the survey results.Females expected inflation at a level of 9,2 per cent, while male respondents expected inflation at a level of 8,9 per cent.
In both 2006 and 2008, higher monthly income earners had higher inflation expectations.In 2006 respondents in the Western Cape, the Free State and Gauteng had the highest inflation expectations, while in 2008, respondents in the North West/Northern Cape, Mpumalanga/Limpopo and the Free State had the highest inflation expectations.
In terms of inflation credibility and income group in both 2006 and 2008, most of those in the R8 000+ income group accepted inflation as accurate.The largest share of those in the two lowest income groups responded that they "don't know" in 2006 and 2008.Based on the demographical breakdown the largest share of those respondents who accepted inflation as accurate in 2006, were those in Gauteng and the Western Cape.When considering respondents' education levels, of those with no schooling and some schooling, between 60 and 80 per cent of respondents reported that they "don't know", while of those who had higher educational attainment, around 40 per cent reported that they "don't know" in 2006, and 50 per cent in 2008.Overall, more respondents with a higher education level reported that they accept historic inflation as accurate.

Determinants of inflation expectations and inflation credibility
Logistic regression results are reported in Table 6 and Table 7 for inflation expectations and inflation credibility, respectively.The model for inflation expectations includes population group, gender, geography (provinces), income groups and age.The dependent variable was coded 1 for inflation expectations between 26 per cent and 100 per cent, and 0 for inflation expectations lower or equal to 25 per cent.The categorical variables are White males between the ages of 25 and 34 living in Gauteng, and who earned an income of between R800 and R3 999 per month.Based on the z-statistics, the results can be interpreted as follows: • Compared to White respondents, Blacks, Coloureds and Asians were more likely to expect an inflation rate of between 25 per cent and 100 per cent in 2006.In 2008, however, Coloureds and Asians were less likely, compared to White respondents, to expect an inflation rate of between 25 per cent and 100 per cent.
• In 2006, compared to Gauteng, respondents in the Western Cape, Eastern Cape and KwaZulu-Natal were less likely to expect a rate of inflation between 25 per cent and 100 per cent.In 2008, respondents in Eastern Cape and the Free State were less likely to expect a rate of inflation between 25 per cent and 100 per cent, while respondents in North West/ Northern Cape were more likely to expect inflation between 25 and 100 per cent, compared to Gauteng.
• Those respondents who were in the highest and second-highest income categories were less likely to expect inflation between 25 and 100 per cent in 2006.In 2008, only the highest income category was less likely to expect inflation falling within this category.Variables included in the logistic model for inflation credibility were population group, gender, province, income, age and education.The reference group is White males between the ages of 25 and 34, with matric, living in Gauteng, and who earned between R800 and R3 999.The results can be interpreted as follows: • In 2006, Blacks were less likely to accept the inflation rate as accurate, compared to White respondents.
• Females were less likely to accept inflation as accurate compared to males in both 2006, and 2008.
• In both 2006 and 2008, respondents in the Eastern Cape, KwaZulu-Natal, Limpopo and North West were significantly less likely to accept inflation as accurate, compared to those in Gauteng.In 2008, respondents in Mpumalanga were also significantly less likely to accept the inflation rate as accurate.
• In both 2006 and 2008, those with no schooling and some schooling were less likely to accept the inflation rate as accurate compared to those with matric.In 2006, respondents with an artisan/technikon/technical qualification were more likely to accept the inflation rate as accurate.
• In 2006, respondents older than 50 years were less likely to accept the inflation rate as accurate.In 2008, however, those between 16 and 24 were more likely to accept the inflation rate as accurate.
• In 2008, those in the lowest income category were less likely to accept the inflation rate as accurate.For all income categories, except the lowest, there was an increase in the probability of accepting the historic inflation rate as accurate between 2006 and 2008, for both males and females.

Multinomial analysis 6
The information from the two surveys can be used to compare the different outcomes between 2006 and 2008.In the inflation expectations survey the aim is to test whether there is a significant difference between the characteristics of those who believe inflation to be below or equal to 25 per cent, those who believe inflation to be above 25 per cent and those who responded that they "don't know", as presented by the BER between 2006 and 2008.Similarly, by using the inflation credibility survey, it is possible to ascertain whether there are differences in the underlying characteristics of those who believe that the current inflation rate is accurate, those who do not believe that the current inflation rate is accurate and those who responded that they "don't know" between the same two periods.Furthermore, it can also be determined whether the same characteristics which impact on inflation expectations, impact on inflation credibility, thereby determining whether there is a possible feed-through effect from inflation credibility to inflation expectations.
A multinomial logit was estimated for the inflation expectations and inflation credibility surveys for both 2006 and 2008.The multinomial logit model is an expansion of a binary-choice model.
A binary-choice model, however, only allows for two possible outcomes in the dependent variable, whereas the multinomial logit model allows for more (Lancaster, 2004).For the inflation expectations survey, the reference group was those who believe inflation to be below or equal to 25 per cent.For the inflation credibility survey, the reference group was those who believe that the current inflation rate is accurate.
The coefficients are estimated by maximum likelihood, and the relative risk ratio (RRR) is reported in Table 8 and Table 9.First, the outcomes from the inflation expectations survey are modelled, followed by the outcomes from the inflation credibility surveys.The same independent variables and benchmark categories were used for both surveys.
The explanatory variables are based on a set of demographic characteristics that could determine how individuals see inflation.The results from the 2008 inflation expectations survey can be compared to the 2006 results as calculated by Rossouw et al. (2009), which is the first South African study against which results can be benchmarked.The variables included in the multinomial analysis were the following: • Gender (reference = male) • Population group (reference = Asians) • Age, with respondents divided into age groups (16)(17)(18)(19)(20)(21)(22)(23)(24), (35-39) and (50+).The benchmark category is (25-34) 7 .
• In terms of spatial distribution, respondents from North West and the Northern Cape are grouped together, as well as those from Mpumalanga and Limpopo, as the original survey data was grouped in this way.Western Cape was set as the benchmark category.For the inflation credibility survey, the provinces were not grouped together, but coded 1 to 8 and the benchmark province (Western Cape) was coded 0.
• Information regarding education was available for respondents in the inflation credibility survey, and was included in the credibility model.Education includes those with some schooling, matric, an Artisan/Technicon/Technical qualification and those with a University degree/Professional (reference = no schooling).
Clarity about the inflation expectations of different groups and their perceptions about the credibility of historic inflation data can assist central banks in targeting more accurately their communication initiatives.This analysis might serve as an early warning of groups with overly high inflation expectations or incorrect perceptions of historic inflation rates that might lead to wage demands exceeding the rate of inflation (see for instance Forsells and Kenny, 2002, on such a link).
For both the inflation expectations and the inflation credibility surveys conducted in 2006, the model show a goodness of fit that is significantly different from zero.The inflation expectations model had a χ 2 value of 150,81 and the inflation credibility model a χ 2 value of 588,86, indicating that not all estimates are jointly equal to zero.In 2008 the values were 185,92 and 495,66 respectively; therefore still significantly different from zero.The Pseudo R 2 value for both models is between 0 and 1.For the inflation expectations model, the Pseudo R 2 in 2006 was 0,0467, and 0,0593 in 2008.The Pseudo R 2 for the inflation credibility model was 0,1035 in 2006 and 0,097 in 2008.As in binomial logistic models, the PseudoR 2 will more than likely fall between 0 and 0,333 (Pindyck and Rubinfeld, 1981).

Expectations model
The relative risk ratios (RRR) for the inflation expectations model for both 2006 and 2008, were analysed at the 90 per cent confidence interval forH 0 : inflation expectations are the same.Table 8 compares the significance and signs from the inflation expectations results for the multinomial logit model for 2006 and 2008.Based on the Zvalues, those categories which were significant at (at least) the 10 per cent significance level will be discussed.
First, this analysis attempts to determine what percentage of which population group thinks that the expected inflation rate is higher than 25 per cent, as opposed to less than 25 per cent.The results are compared between 2006 and 2008.The output from the regression in Table 8 suggests that the odds in this respect are 171 per cent [i.e.100(1-0,365)] less for Whites than for Blacks in 2006.In 2008, however, there was no significant difference between Whites and Blacks.In 2006 the coefficient for Asians was significant and positive, implying that the odds were higher for Asians perceiving the inflation rate to be higher than 25 per cent, compared to Blacks.However, during the 2008 survey round, the odds were 78,2 per cent less for Asians than for Blacks in this regard.
Similarly, an attempt is made to compare between 2006 and 2008 the percentage of which gender group thought that the expected inflation rate was higher than 25 per cent, as opposed to less than 25 per cent.It seems that gender did not influence respondents' decisions significantly on whether they expected inflation to be above or below 25 per cent in both 2006 and 2008.There is therefore in 2006 no significant difference between the inflation expectations of males and females, and only a statistically insignificant difference in 2008, although mean inflation expectations for females were higher than for males.
The same structure is applied to determine what percentage of which age group thinks that expected inflation will be higher than 25 per cent, rather than less than 25 per cent, for both 2006 and 2008.Similar to gender, it seems that in both 2006 and 2008 age did not influence respondents' decisions significantly on whether they expect inflation to be above or below 25 per cent.There is therefore, between 2006 and 2008, no significant difference between the inflation expectations of different age groups.
In terms of the income variable, in 2006 the odds of perceiving the inflation rate to be higher than 25 per cent decreased by 72,1 and 53,6 respectively, for those who earned in the top two income brackets, compared to those who earned in the lowest income bracket.A similar result was obtained during 2008, although only the coefficient for those in the top income category was significant and the increase in the odds was slightly less.
The odds of expecting an inflation rate above 25 per cent for respondents in Gauteng increased by 126, compared to those in the Western Cape.In 2008, however, the odds were higher for KwaZulu-Natal and North West/Northern Cape to expect inflation above 25 per cent, compared to the Western Cape.In 2008, the odds of expecting inflation above 25 per cent decreased by 86 for those in the Eastern Cape.
Second they expected the inflation rate to be, as opposed to those who thought that the actual inflation rate was lower than 25 per cent, no significant difference was seen between the responses by male and female respondents in both survey years.
When considering the income variable, in 2006 the odds was less by 41,4 that the highest income group "did now know" what they expected the inflation rate to be, as opposed to those who thought that the expected inflation rate was lower than 25 per cent.In 2008, the odds were significantly lower that high-income individuals responded that they "did not know", compared to those in the lowest income group.
The odds were higher by 50,5 for respondents in the Free State to respond that they "did now know" what they expected the inflation rate to be, as opposed to those who thought that the expected inflation rate was lower than 25 per cent.The odds were around 37,4 less for respondents in Gauteng in 2008.

Credibility model
The RRR were calculated for the two outcomes of the inflation credibility surveys for both 2006 and 2008.The RRR were evaluated at the 90 per cent confidence interval on a null hypothesis H 0 : inflation credibility is the same for all respondents.Table 9 displays the results of an inflation credibility multinomial logit regression model for 2006 and 2008.Based on the Zvalues, those categories which were significant at (at least) the 10 per cent significance level will be discussed.
First, this analysis attempts to determine what percentage of which gender group did not accept the inflation rate as accurate, in comparison with those who did accept it as accurate.The results are then compared between 2006 and 2008.The output from the regression, as shown in Table 9, suggests that the odds in this respect in 2006 were 30,1 per cent higher for females than for males.In 2008, however, there was no significant difference between male and female participants.In 2006 the coefficient for the age group 16-24 was not significant; however, in 2008 the odds were 31,3 per cent lower for this group.The results further suggest that the odds in 2006 were 41,5 per cent higher for participants over 50 years to not accept inflation as accurate than for those between 25-34.In 2008, the odds for this group, however, was 28,6 per cent less.In 2006, the odds increased by 33,3 for Coloureds to not accept the inflation rate as accurate, compared to Blacks.In 2008, the odds increased even more, by 113,2 per cent for Coloureds not to accept the inflation rate as accurate, compared to Blacks.In 2008, the odds were also 80,4 per cent higher for Asians to not accept the inflation rate as accurate, ceteris paribus, and compared to the benchmark category, Blacks.
In 2006, the odds were significantly less for those with any type of education to not accept the inflation rate as accurate, compared to those with no education.However, in 2008, none of the education coefficients were found to be significant.
In 2008, the odds decreased by 50,1 per cent for respondents in the Free State to not accept the inflation rate as accurate, compared to those in the Western Cape.In the same period, the odds were higher for KwaZulu-Natal (58,7 per cent), Mpumalanga (275,7 per cent) and Limpopo (317,9 per cent) to not accept the inflation rate as accurate.
Second, this analysis attempts to determine the difference between the 2006 and 2008 survey results in terms of what percentage of which gender group "did not know" whether they accepted the inflation rate as accurate or not, compared to those who did accept it as accurate.The results show that in 2006 and 2008 the odds increased by 101,2 per cent and 35,3 per cent, respectively, for female participants, as compared to males in this regard.Similarly, there is an attempt to determine what percentage of which population group "did not know" whether they accepted the inflation rate as accurate or not, compared to those who did accept it as accurate.The output shows that the odds decreased by 72,5 per cent for Whites to "not know", as opposed to Blacks in 2006.In 2008 the odds decreased by 43,1 for this group, compared to the reference group.On the other hand the odds in 2006 were 43,3 per cent more for Asians, than for Blacks to "not know".In 2008, the coefficient for Asians was not significant.In 2006, the odds for Coloured respondents to "not know" was also lower with 44,4 per cent, compared to Blacks.This coefficients was, however, not significant in 2008.
This analysis also considers what percentage of which age group "did not know" whether they accepted the inflation rate as accurate or not, compared to those who did accept it as accurate.
The results show that the odds in 2006 increased by 32,4 per cent for participants older than 50 years, compared to those between 25-34 years.In 2008, there was no significant difference between those older than 50 years and those 25-34.In 2008, however, the odds decreased in this respect for those between 16-24 by 40,0 per cent, compared to the benchmark category 25-34.
In both 2006 and 2008, the odds were significantly less for those with any type of education to respond that they "did not know", as opposed to accepting the inflation rate as accurate, compared to those with no education.
In 2006, the odds were higher that respondents in the Eastern Cape (145,4 per cent), KwaZulu-Natal (53,6 per cent), Limpopo (94,4 per cent) and the North West (78,5 per cent), would respond that they "did not know" if they accepted the current rate of inflation as accurate, compared to those in the Western Cape.In 2008, however, compared to the Western Cape, all provinces showed significant increases in the odds of "not knowing" if they accepted the inflation rate as accurate, except for the North West.
Furthermore, the odds that respondents "did not know" decreased by 26,5 and 27,5 respectively, for those who earned between R800-R3 999 and R4 000-R7 999.In 2008, the odds in this regards were significantly lower for all income groups, ceteris paribus.
Based on these null hypotheses, it transpires that sub-categories increase the use of information within surveys of inflation credibility in both 2006 and 2008.This approach highlights considerable differences in perceptions between sub-categories of respondents, as well as changes in perceptions between different survey periods.The results show that in 2006, when the average inflation rate was 5,4 per cent, respondents seemed less likely to believe that the inflation rate is accurate, whereas in 2008, when the average inflation rate was 13,7 per cent, respondents were more likely to accept the inflation rate as accurate.

Conclusions
Inflation expectations and inflation credibility of male and female respondents differed between 2006 and 2008.In one instance (2008) relatively lower inflation credibility among female respondents fed into relatively higher inflation expectations, but this was not the case in the surveys undertaken in 2006.This difference should be reconsidered once more inflation credibility surveys have been completed for comparison with the results of inflation expectation surveys.
This paper employs a logit model and a multinomial analysis of domestic inflation credibility surveys to test a hypothesis that inflation expectations and inflation credibility do not vary between gender, population and age groups and other characteristics.The analysis further aimed to test whether respondents' inflation expectations and perceptions of accuracy were influenced by different sample periods and different average inflation rates at the time.
The results from the logit models showed that, compared to Blacks, all population groups were more likely to expect an inflation rate of between 25 and 100 per cent during 2006.Furthermore, respondents in the Western Cape, Eastern Cape and KwaZulu-Natal, as well as those in the two highest income groups, were less likely to expect inflation to be between 25 and 100 per cent.In 2008, Coloured and Indian respondents, and those in the Eastern Cape and Free State, as well as those in the highest income category were less likely to expect inflation between 25-100 per cent.In terms of inflation credibility, Blacks, females, those in the Eastern Cape, Limpopo, North West, as well as those with no schooling, some schooling, artisan qualification and those older than 50 years were less likely to accept the inflation rate as accurate.In 2008, females, those in the Eastern Cape, KwaZulu-Natal, Mpumalanga, Limpopo and those with no schooling and some schooling, were less likely to accept inflation as accurate.Those between the ages of 16 and 24 years were more likely to accept inflation as accurate during 2008.
The results from the multinomial analysis showed that inflation expectations between 2006 and 2008 are significantly different, especially between different population groups.No significant difference was, however, noted in 2008, for both the inflation expectations and inflation credibility surveys, as opposed to 2006, when inflation credibility showed a statistically significant difference between males and females.The results varied significantly between the sample periods.An explanation could be that the level of inflation used in the survey questions was lower in 2006 than in 2008, and respondents based their expectations on these values.In addition, in 2008, when the stated inflation rate was at a double-digit level, respondents were less likely to not perceive the inflation rate as accurate, whereas in 2006, they were more likely to not perceive the inflation rate as accurate.If a breakdown in inflation credibility spreads across countries, the use of inflation credibility surveys might gain popularity.Once more credibility surveys have been conducted over time and under different inflationary conditions in South Africa, it would be possible to compare the influence of different inflationary environments.
The statement and question used in the inflation credibility surveys should be amended to ensure a better alignment with the statement and question used in inflation expectation surveys.This can be achieved through the use of two statements/questions in the next biennial inflation credibility survey planned for 2010, one of which will be aligned to the statement/question used in inflation expectation surveys.This reformulation will provide some respondents with an opportunity to indicate whether they think prices increased at a rate higher or lower than the historic rate of inflation.
It is striking that the acceptance of historic inflation figures as accurate is low in a low-inflation environment.This seems to indicate that respondents confuse price levels and price increases (i.e.inflation).This is an area for further research, as it might have implications for inflation targeting as a policy regime.
Income     Outcome 0 (think that the actual inflation rate is below 25 per cent) is the base outcome.The reference groups are Asians, males, and those between the ages of 25-34.
Results in brackets denote z-statistics.*Significant at the 10% level, **Significant at the 5% level, ***Significant at the 1% level Sources: BER; own calculations   Reference group: respondents between the age of 35-49, with some schooling who earned between R4000-R7999 and lives in the Western Cape.Reference group: Blacks respondents between the age of 35-49, with some schooling who earned between R4000-R7999 and lives in the Western Cape.
Reference group: respondents between the age of 35-49, who earn between R4000-R7999 and live in the Western Cape.Reference group: respondents between the age of 35-49, with some schooling who earned between R4000-R7999 and lives in the Western Cape.Reference group: Black respondents between the age of 35-49, with some schooling who earned between R4000-R7999 and lives in the Western Cape.

Figure 1 .
Figure 1.1 to Figure 1.4 represent the change in the probability of expecting inflation between 25 per cent and 100 per cent.Overall, the probability of expecting inflation between 25 per cent and 100 per cent increased more for Black and White females in 2008 than in 2006.The increase in the probability for White males was also higher in 2008.For both males and females, in the bottom two income categories, the probability of expecting inflation between 25 per cent and 100 per cent in 2008, was lower compared to 2006.

Figure 2 .
Figure 2.1 to Figure2.4 represents the change in the probability of accepting the historic inflation rate as accurate.In 2008, for males and females, the increase in the probabilities of accepting the inflation rate as accurate for all populations groups, except for Coloureds, was higher than in 2006.For all income categories, except the lowest, there was an increase in the probability of accepting the historic inflation rate as accurate between 2006 and 2008, for both males and females.
for Economic Research, 2006 and 2008 Although the survey used South African inflation data, Statistics South Africa calculate inflation rates, inter alia for the country's nine provinces.For 2005 the headline (or overall) inflation rate was 2,4 per cent for the Eastern Cape, 2,9 per cent for the Free State, 3,4 per cent for Gauteng, 2,5 per cent for KwaZulu Natal, 2,1 per cent for Limpopo, 3,7 per cent for Mpumalanga, 3,5 per cent for the North West, 4,2 per cent for the Northern Cape and 3,2 per cent for the Western Cape.For the individual provinces the rates of inflation in 2007 were 6,6 per cent in the Eastern Cape, 6,7 per cent in the Free State, 6,5 per cent for Gauteng, 7,0 per cent in KwaZulu Natal, 7,4 per cent for Limpopo, 7,7 per cent for Mpumalanga, 7,1 per cent in the North West province, 6,5 per cent in the Northern Cape, and 7,1 per cent in the Western Cape.

Figure 1 . 2 Figure 1 . 1
Figure 1.2 Increase in the probability of males expecting inflation between 25-100 per cent by population group, 2006 and 2008

Figure 1 . 3
Figure 1.3 Increase in the probability of females expecting inflation between 25-100 per cent by income group, 2006 and 2008

Figure 2 . 1
Figure 2.1 Increase in the probability of females accepting the inflation rate as accurate by population group, 2006 and 2008

Figure 2 . 3
Figure 2.3 Increase in the probability of females accepting the inflation rate as accurate by income group, 2006 and 2008

Figure 1 . 4
Figure 1.4 Increase in the probability of males expecting inflation between 25-100 per cent by income group, 2006 and 2008

Figure 2 . 2
Figure 2.2 Increase in the probability of males accepting the inflation rate as accurate by population group, 2006 and 2008

Figure 2 . 4
Figure 2.4 Increase in the probability of males accepting the inflation rate as accurate by income group, 2006 and 2008 Leeper (2003).(2008)andLeeper (2003)assess various aspects of inflation targeting, but do not mention surveys or other techniques employed by central banks to obtain data on inflation expectations.Literature dealing with the communication strategies of central banks (see for instance Bank of International Settlements, 2008; Blinder and Wyplosz, 2005; or Ehrmann and Fratzscher, 2005) does not analyse inflation expectations of different groups in inflation-targeting countries.Rossouw et al. (2009) pointed out that central banks in the cluster of inflation-targeting countries use different approaches to obtain a measure of inflation expectations.Inflation expectations are assessed by means of: (Brachinger, 2005ifferentials on different classes of traded financial assets by one central bank (Slovakia);• interest rate differentials on different classes of traded financial assets and surveys of inflation expectations by eight central banks (Canada, Chile, Colombia, Iceland, Israel, Mexico, Sweden and Thailand);• surveys of inflation expectations by thirteen central banks (Australia, Brazil, Czech Republic, Ghana, Hungary, Indonesia, New Zealand, Norway, Peru, Philippines, Poland, Romania and South Korea); and• interest rate differentials on different classes of traded financial assets, surveys of inflation expectations and inflation forecasts by two central banks (South Africa 2 and United Kingdom).The credibility of inflation figures receives little attention in inflation-targeting countries and, therefore, in the academic literature.Only New Zealand and Sweden officially survey inflation credibility(Brachinger, 2005; Jonung, 1981; Palmqvist and Stromberg, 2004; and Reserve Bank of New Zealand, [S.a.]).Since 1985 the Reserve Bank of New Zealand surveys perceptions of the accuracy of the historic rate of inflation of individual respondents on a quarterly basis (Reserve Bank of New Zealand, [S.a.] (National Gambling Board, 2005)t published in the Bank's bi-annual Monetary Policy Review (see for instance SA ReserveBank, 2008), but are published by the BER.The Bank publishes only inflation forecasts of financial market analysts, trade unionists and business enterprises, and inflation expectations calculated from interest rate differentials on different classes of traded assets.The BER uses AC Nielsen to survey individual responses through face-to-face interviews on its behalf as part of omnibus surveys3.This approach ensures a representative survey, which would not be possible by means of telephone or postal surveys(National Gambling Board, 2005).This paper reviews only survey results for the fourth quarters of 2006 and 2008, thereby aligning it to the two domestic biennial surveys of inflation credibility undertaken during the same periods.It is important to keep the planning time frame in mind, as the latest available historic inflation data at the time of planning the research was used for sampling purposes.Salient features of the sampling results are summarised in Table 5,1 per cent per year.During 2005 prices increased by 3,5%.By how much do you expect prices in general to increase in 2006?" (Bureau for Economic Research, 2006: 19).For the second review period (last quarter of 2008) respondents were asked to respond to "over the past five years prices increased by on average 4,5 per cent per year.During 2007 prices increased by 7,0%.By how much do you expect prices in general to increase in 2008?" (Bureau for Economic Research, 2008: 19).
, this analysis attempts to draw a comparison between 2006 and 2008 in terms of what percentage of which population group "did not know" what they expected the inflation rate to be, over those who expected an inflation rate lower than 25 per cent.The output from the regression shows that the odds for Whites was 42,7 per cent less in this regard, compared to Blacks.In 2008, however, there was no significant difference between the inflation rates expected by Whites and Blacks.It was then attempted to determine what percentage of which age group "did not know" what they expected the inflation rate to be, as opposed to those who thought that the expected inflation rate was lower than 25 per cent.The results suggests that the odds in 2006 were 60,4 per cent higher for respondents in the age group 35-49 than for those in the age group 25-34.Moreover, the odds increased by 44,7 per cent for people older than 50 years, in comparison with those in the age group25-34.In 2008, the output from the regression shows that the age group had no significant impact on inflation expectations.When considering what percentage of which gender group "did not know" what

Table 1 :
Average of responses about inflation expectations according to age, gender, population group and the total, 4 th quarter 2006 and 2008

Table 2 :
Average of responses about inflation expectations according to gender, and Black and Whites, 4 th quarter 2006 and 2008

Table 3 :
Responses about inflation credibility according to age, gender, population group and the total, 4 th quarter 2006 Markinor, 2006Markinor, 2006

Table 4 :
Responses about inflation credibility according to age, gender, population group and the total, 4 th quarter 2008

Table 5 :
Responses about inflation credibility according to gender and Black and White population groups, 4 th quarter 2006

Table 8 :
Output from the multinomial regression model for inflation expectations 2006 and 2008