the price level as unchanged (and which obviously should correspond to the case of zero inflation). Wynne (2005) takes advantage of this unambiguous relation between the qualita-tive responses and the quantitaqualita-tive HICP index to gauge the size of the bias: the instances when the qualitative responses to the HCS in a given country and year state perceptions of unchanged prices (thus a perception of absence of inflation), one can compare this outcome with the annual change in the HICP in the same country and year. If perceptions of changes in the HCS are a correct summary measure of price developments, one could then attribute the extent to which the HICP is above zero to the measurement bias in the HICP. This com-parison is at the core of the results in Wynne (2005).
6. In implementing this approach to gauging the HICP bias, Wynne (2005) takes two intermedi-ate steps: he first constructs an index number which summarises the stintermedi-ate of perceptions of inflation by households by means of a balance of responses in the HCS in a given country and year. This provides the survey-based data points measuring perceptions of inflation in countries and time. Each of these data points are linked one to one to the corresponding out-turn for HICP inflation in that country and year, leading to a cluster of data points showing the observed relation between HICP outturns and HCS based measures of expectations. In a second step, Wynne (2005) fits a non-parametric kernel regression (with HICP as the fitted variable and the HCS index as the regressor) to such cluster of data points, and then checks the value fitted for HICP when the index takes the value of zero (i.e. the value of the index corresponding to “perception of unchanged price level or equivalently zero inflation”). As a result of these steps, the approach obtains that the measurement bias calculated according this criterion would be between 1% and 1.5% annually. This range appears to be considerably above the available rough estimates of the HICP measurement bias.4
7. Overall, implementing a higher number of methodologies to assess the size of a potential measurement bias in the HICP permits the cross-checking of the various results and thus to enhance the robustness of the assessments. At the same time, relating the specific range esti-mate for the bias mentioned above, much caution needs to be exerted, as it is also the case for all attempts thus far to gauge the size of the HICP bias. In what follows, we aim at pointing at possible caveats that would seem applicable to the approach in Wynne (2005) described above and which underline the need for caution. We also briefly discuss possible avenues that in our view may serve to address some of the caveats and might thus be useful to researchers in future extensions of this complementary approach to assessing the precision of the HICP.
7.1. First, it needs to be noted that the HCS and the HICP were in principle not designed to measure the same phenomenon or answer the same question. Therefore, even if both indices were fully accurate, still disparities could arise as they are not fully aligned in their ultimate purpose: While the HCS means to respond to the question of how house-holds perceive changes in the cost of living, the HICP, which is not designed as a Cost-of-Living CPI, aims to measure the changes in prices in monetary transactions, excluding items directly affected by monetary policy decisions such as interest rates.5 Such difference in scope could therefore mean that certain disparities are possible even under perfect measurement in both the HCS and the HICP: for instance, interest rate changes or changes in residential property prices could affect more directly an HCS-based index of price level changes than the HICP.
7.2. Second, an additional challenge that needs to be recognised and addressed in measuring perceptions of inflation by households relates to the wide disparity in responses across households, even for households which are regionally close – and thus face comparable conditions as regards price developments. In practice, such disparity in perceptions is addressed by computing a weighted average of responses, i.e. the so-called balance of responses, which gives a certain weight to the various responses and adds them up. Such emphasis on the aggregation of responses should not mask that households do provide considerably different responses to the same question and such variety of responses advises for exerting caution when interpreting the results.
7.3. Third, and foremost, one needs to recognise limitations and potential measurement imperfections also in survey based indicators of inflation perceptions. Indeed, a measure
PROCEEDINGS IFC WORKSHOP – SESSION 7
of price level changes based on indices constructed on the basis of HCS data might also be affected by a measurement “bias”. Two possible sources of such possible bias are often quoted: first, households may weigh more heavily the more frequently purchased items. If, in a certain period, items, which are purchased with higher frequency (such as gasoline, tobacco or restaurant services) experience relatively higher price increases compared to items usually purchased less frequently (such as durable goods), a percep-tion bias may arise. Second, the changeover to euro coins and banknotes, which took place in the first months of 2002, may plausibly also have had a direct bearing on the formation of household perceptions about changes in consumer prices, over and above any direct true impact of the changeover on prices.6
8. The previous considerations however do not necessarily suggest abandoning the approach of using survey based data on perceptions for the purpose of assessing the accuracy of the HICP.
Rather, they point to the possibility of addressing some of these concerns in further efforts to expand the number of methodologies in this area. While the purpose of this note is not to advance new methods to address the above mentioned concerns, some possibly relevant ele-ments in that discussion on methods are provided.
8.1. Relating the point in paragraph 7.2 above and relating purely to descriptive aspects of the data in the HCS, it would seem possible and desirable to explore in further detail – compared to the usually reported balance of responses in the form of a weighted aver-age of responses – the best way to represent by means of summary statistics the infor-mation in the HCS survey regarding perceptions of inflation. In particular, it would seem natural and useful that, in characterising the mean response to the question on inflation perceptions at a given point in time, the information on dispersion of responses is taken into account.
8.2. Relating the point in paragraph 7.3 above, it would seem also important to allow in the analysis of the information in the HCS in connection to inflation perceptions for the possibility of potential “cognitive biases”, by which households would, at least episod-ically, perceive inflation in a not fully accurate manner. Along the lines mentioned above, it would seem possible to elaborate on the analysis of the factors which may underpin such potential cognitive bias in inflation perceptions, such as i) the specific weights which household attach to items in connection with the frequency of purchases, ii) pos-sibly also the (country-specific) algebraic complexity involved in the conversion from legacy currencies to the euro, or, iii) the possibility of instances of monetary illusion (or disillusion) if some households could tend to report as perceived higher inflation what in reality corresponds to more general losses in real disposable income also related to lower growth in nominal wages.
9. In conclusion, it would seem that the “knowledge gap” about the potential measurement bias the euro area’s HICP has not closed over the last few years. In this respect, it would seem desirable that the vitality which this area of research experienced in the period 1998–2003 could be regained, taking into account the importance of the underlying issues both from an economic welfare and policy perspectives. In this respect, new contributions to the literature seem to provide possible further avenues to estimate the HICP bias, by adapting for the euro area work by the Fed in this field (see Lebow and Rudd (2003)) and possibly also by refin-ing the approach proposed by M. Wynne (2005) usrefin-ing survey data. Relatrefin-ing the latter, the general point made in Wynne (2005) – using and cross checking information from various sources should serve well the enhanced assessment of the HICP accuracy – seems important and potentially very fruitful in particular if the potential biases and shortcomings specific to measures of inflation of perceptions based on information in the HCS are taken into account in such an assessment. Indeed, to the extent that the traditionally discussed potential “biases”
in the HICP (i.e. substitution, outlet, aggregating formula biases, etc.) are of different nature that the potential “cognitive biases” in the HCS-based measures of inflation perception, it would seem plausible to augment or enrich the analysis in Wynne (2005) to deliver such an enhanced assessment of accuracy in the HICP. Such approach would indeed seem to merit much further attention.
6 For an analysis of how stated perceptions of inflation may be subject to cognitive biases see Ehrmann (2006).
DIEGO RODRIGUEZ-PALENZUELA
References
Hoffmann, J (1998), “Problems of Inflation Measurement in Germany”, Discussion Paper 1/98, Economic Research Group of the Deutsche Bundesbank.
Camba-Méndez, G, Gaspar, V and Wynne, M (2001), “Measurement Issues in European Consumer Price Indices and the Conceptual Framework of the HICP”, ECB and CEPR.
Wynne, MA and Rodríguez-Palenzuela, D (2004), “Measurement Bias in the HICP: What do we know and what do we need to know?”, Journal of Economic Surveys, Vol. 18, No. 1, February.
Cecchetti, SG and Wynne MA (2003), “Defining Price Stability”, Economic Policy 37, October.
Wynne, M (2005), “An estimate of the measurement bias in the HICP”, Mimeo, Federal Reserve Bank of Dallas.
Forsells, M and Kenny, G (2004), “Survey expectations, rationality and the dynamics of Euro Area infla-tion”, Journal of Business Cycle Measurement and Analysis, Vol. 1, No. 1, 13–41.
Ehrmann, M (2006), “Rational inattention, inflation developments and perceptions after the Euro cash changeover”, ECB Working Paper No. 588, February.
Lebow, D and Rudd, J (2003), “Measurement error in the Consumer Price Index: Where do we Stand?”, Journal of Economic Literature, Vol. 41, March.
Diego Rodriguez-Palenzuela (European Central Bank)