ChatBot

The general contribution of this thesis is the suggested solutions to problems with price measurement, particularly in how to compare service providers that offer (multiple) tariff plans. It is shown how prices can be compared efficiently among several tariff plans from different providers. This issue rarely finds a place in the scientific literature. Technical manuals of statistical offices or other organisations, if available, predominantly suggest the use of consumption profiles to compare service prices.

Though all analysed prices result from tariff plans, the three projects are quite independent, and thus the major contributions are contained in the specific applications. For mobile communication services and public transport, two innovative index concepts are suggested and empirically tested. In the con-text of administered prices, standard consumption profiles are used to compare

139

CHAPTER 5. SUMMARY 140

service prices. There, the relevant contribution is the economic analysis of ser-vice prices in Swiss municipalities. The most important findings and issues for further research of each project are summarised below. To avoid redundancy with the general introduction in chapter 1 and the summaries of each specific chapter, this section focuses only on the most important points.

Hedonic price indexes for mobile communication

By applying hedonic price indexes to compare tariff plans of mobile commu-nication providers, all characteristics of the extremely diverse contracts are consistently implemented in the price comparison. The presently used con-sumption profile methods are not capable of doing so, and they ignore major characteristics, which results in biased price comparisons.

As this is a first application of hedonic price indexes for mobile communication, different model specifications are estimated with several methods. Because consumption is dependent on the tariff plans, the double-imputed indexes use symmetric index formulas to treat all providers equally. All resulting indexes indicate that Swisscom has significantly lower implicit prices than Orange for the given sample. This contradicts official statistics. Possible reasons are that Orange consumers are not in efficient tariff plans, Swisscom offers more attractive tariff plans for students or Orange adapts its tariff plans to the consumption profiles of the Federal Office of Communications. For further research, non-parametric model specifications might be particularly interesting to improve the prediction accuracy. Additionally, several practical issues give rise to important open questions, such as determining optimally the discount on the phone price.

The kilometer price index for public transport

The kilometer price index for public transport describes the implicit price for an averagely consumed kilometer with a specific provider. The concept is straightforward and easily communicable to a broad public. Currently used price indexes for public transport in Switzerland use profiles and compare ex-plicit prices of tickets. These methods are undocumented, and they suffer from the same problems as all other indexes based on profiles.

In the results, the presented kilometer price index estimates implicit price in-creases to be lower than the other methods do. In years without any tariff change, implicit prices may even fall, which is not perceived at all by the pub-lic. More than 50% of all kilometers are travelled by people possessing a GA travelcard. Though its explicit price has been raised significantly, the implicit kilometer price increased by only 4% between 2007 and 2011. The major rea-son for this observation is that consumers travel more with the same GA tariff plan, mainly because the quality and speed of connections increased. These increases are implemented in the index and consequently result in lower implicit kilometer prices. Ticket types with smaller weights in the index contributed more to the general implicit price increase measured by the KMI, even though their explicit prices were not raised that much. In further applications of this concept, one should mainly invest in the data structure and, separate first-and second-class tickets into different accounts.

Administered prices of basic services in Swiss municipalities

Prices for electricity, waste management, water supply and sewer water ser-vices are paid by every household each year. A representative two-person household pays in average slightly more than 1^′000 Swiss francs for these four services. The services are provided by local monopolists, and the prices are administered by governments. Because the prices for four different services among 324 Swiss municipalities are compared, the profile method is applied.

Three standardised households are used to determine the profiles and mea-sure service prices for different consumption intensities. The resulting index shows significant differences in service prices across municipalities. Because the prices are administered and should respect the benefits as well as the cost recovery principles, these differences are analysed.

The service price differences are explained by several municipality character-istics. The most robust result is that municipalities with a high tax burden usually also show high service prices. In addition, the municipalities in cantons with strong financial control tend to show lower administered prices. Both results are heavily dependent on cantonal clusters and should be interpreted cautiously. There is no sign that economies of scale result in lower service prices or that these service prices capitalise in rents. This analysis provided

CHAPTER 5. SUMMARY 142

an alternative perspective on user charges, which generate part of non-tax government revenue. In further research, particularly the cantonal variables omitted in the estimations should be investigated and discussed. To compare municipalities with regard to several fiscal and financial variables from a house-hold perspective, a cost-of-living index, including tax rates, rents, education and healthcare costs could be constructed. As a result, municipalities could be evaluated precisely by including these important variables jointly. Additionally, this concept could be used to create a website to support household deci-sion making about where to live, according to household type, income and workplace.