How to Measure Living Standards and Productivity

This paper sets out a general algorithm for calculating true cost-of-living indices or true producer price indices when demand is not homothetic, i.e. when not all expenditure elasticities are equal to one. In principle, economic theory tells us how we should calculate a true cost-of-living index or Konüs price index: first estimate the consumer's expenditure function (cost function) econometrically and then calculate the Konüs price index directly from that. Unfortunately this is impossible in practice since real life consumer (producer) price indices contain hundreds of components, which means that there are many more parameters than observations. Index number theory has solved this problem, at least when demand is homothetic (all income elasticities equal to one). Superlative index numbers are second order approximations to any acceptable expenditure (cost) function. These index numbers require data only on prices and quantities over the time period or cross section under study. Unfortunately, there is overwhelming evidence that consumer demand is not homothetic (Engel's Law). The purpose of the present paper is to set out a general algorithm for the nonhomothetic case. The solution is to construct a chain index number using compensated, not actual, expenditure shares as weights. The compensated shares are the actual shares, adjusted for changes in real income. These adjustments are made via an econometric model, where only the responses of demand to income changes need to be estimated, not the responses to price changes. This makes the algorithm perfectly feasible in practice. The new algorithm can be applied (a) in time series, e.g. measuring changes over time in the cost of living; (b) in cross section, e.g. measuring differences in the cost of living and hence the standard of living across countries; and (c) to cost functions, which enables better measures of technical progress to be developed.consumer price index, Konüs, cost of living, measurement of welfare change, Quadratic Almost Ideal Demand System, producer price index, homothetic, Productivity

Chain Indices of the Cost of Living and the Path-Dependence Problem: An Empirical Solution

This paper proposes an empirically feasible method for correcting the path-dependence bias of chain indices of the cost of living. Chain indices are discrete approximations to Divisia indices and it is well known that the latter are path-dependent: the level of a Divisia index is affected not just by the level of prices at the two endpoints but also by the path between the endpoints. It is also well-known that a Divisia index of the cost of living is path-independent if and only if all income elasticities are equal to one, a restriction that is decisively rejected by studies of consumer demand. In theory, the true cost of living index (or Konüs price index) could be derived by estimating the expenditure function. But this seems impractical due to data limitations: the number of independent parameters rises roughly in proportion to the square of the number of commodities and consumer price indices contain hundreds of items. This paper shows how this problem can in fact be overcome empirically using a flexible model of demand like the "Quadratic Almost Ideal Demand System". The proposed method requires data only on prices, aggregate budget shares and aggregate expenditure. The method is applied to estimate Konüs price indices for 70 products covering nearly all the UK's Retail Prices Index over 1974-2004, with each year in turn as the base. The choice of base year for utility is found to have a significant effect on the index, even in the low inflation period since 1990.Index number, cost of living, Divisia, Chain, Path-dependence, Almost Ideal Demand System

Ex Post Versus Ex Ante Measures of the User Cost of Capital

When doing growth accounting, should we use ex post or ex ante measures of user costs to calculate the contribution of capital? The answer, based on a simple model of temporary equilibrium, is that ex post is better in theory. In practice researchers usually calculate ex post user costs by assuming that the rate of return is equalised across assets. But this is only true if expectations are correct. A numerical example shows that either ex ante or ex post can be closer to the true measure, depending on the parameters. I propose a hybrid method that makes use of elements of both approaches. I test this and the other methods using data for 31 UK industries.User cost, capital, ex post, ex ante, growth accounting

Understanding the space–time (in)consistency of the national accounts

Space–time consistency means that an earlier PPP, updated by relative inflation rates, equals a more recent PPP. I show that in the absence of data errors Divisia price indices are space–time consistent provided that the consumer’s utility function is homothetic

GDP and the system of national accounts: past, present and future

China became the world’s largest economy in 2014”. “UK GDP grew by 0.2% in the first quarter of 2017”. “In the eurozone, inflation as measured by the Consumer Price Index was 1.4% in the year to May 2017”. Any scanner of websites that cover business news can read statements like these on any day of the week. Each statement relies on modern economic statistics whose basis is the System of National Accounts (SNA). In this chapter I briefly outline how the SNA came to have such a powerful (if background) role. I then go on to discuss some of the many criticisms levelled at the SNA, and in particular at GDP, its centrepiece. These criticisms fall into two groups. The first group raises doubts about how accurately GDP is measured. The second is more about the re levance of GDP (and the SNA) as a guide to policy. Even if GDP is measured accurately, is it measuring anything which thoughtful people should be interested in

Prospects for UK growth in the aftermath of the financial crisis

Introduction The UK economy went into recession in 2008Q2. GDP fell in that quarter and continued falling for the next five quarters. It stopped falling in 2009Q3 and began growing again, but so slowly that in 2013Q1 its level was still 4% below the previous peak in 2008Q1 (see Table 1.1). The fall in GDP per capita has obviously been even larger, since the population has continued to grow. The whole period since 2008Q1 therefore justifies the term ‘slump’ or even ‘depression’. Few if any commentators expected a slump of this severity prior to its start. After it became apparent that the recession, though deep, was over, many expected the recovery to be equally rapid. But this didn’t happen. The recovery has been slow and is still incomplete. There have been many surprising features of the five or so years since the recession began. First, despite the massive fall in output, unemployment rose comparatively modestly from 5.2% in 2008Q1 to a high of 8.4%; in September-November 2013 it was 7.1%. Second, employment and total hours worked, after falling initially, have been robust: employment and hours are both now higher than at the peak (Figures 1.1 and 1.2). The flip side of these facts is the productivity puzzle: not only has labour productivity (whether measured on an hours basis or a heads basis) stopped growing, its level has actually fallen. In 2013Q1 GDP per hour worked was still 5% below its peak level (Figure 1.4). All this calls into question the future prospects of the UK economy, which seemed so bright during the boom. Was it all just an illusion? This is the question on which I hope this chapter will throw some light. In 1995 I published an article with the somewhat sceptical title ‘Supply side reform and UK economic growth: what happened to the miracle?’ (Oulton, 1995). I argued that up till the end of the 1970s the growth of the British economy had been hampered by two factors: first, our dysfunctional system of industrial relations and second a low level of investment in human capital. Despite the title, my conclusion was upbeat

Measuring productivity: theory and British practice

This paper lays out the basic theory behind productivity measurement, whether at the level of the country, region, industry or firm. The theory is illustrated using recent data from UK official publications. Productivity growth over time and differences in productivity levels between countries or regions at a point in time are both covered. Labour productivity and multi-factor productivity (MFP) are discussed. In the case of MFP special attention is paid to the measurement of capital inputs. Wherever possible, an accompanying spreadsheet supplies data from recent publications by the United Kingdom’s Office for National Statistics so that readers can reproduce official estimates or even employ alternative assumptions to produce their own estimates. Limitations in the underlying theory are highlighted as are empirical difficulties in implementing the theory

Rates of Return and Alternative Measures of Capital Input: 14 Countries and 10 Branches, 1971-2005

We employ the EU KLEMS database to estimate the real rate of return to capital in 14 countries (11 in the EU, three outside the EU) in 10 branches of the market economy plus the market economy as a whole. Our measure of capital is an aggregate over seven types of asset: three ICT assets (computers, communications equipment, and software) and four non-ICT assets (machinery and equipment, nonresidential structures, transport equipment, and other). The real rate of return in the market economy does not vary very much across countries, with the exception of Spain where it is exceptionally high and in Italy where it is exceptionally low. The real rate appears to be trendless in most countries. Within each country however, the rate varies widely across the 10 branches, often being implausibly high or low. We also estimate the growth of capital services by two different methods: ex-post and exante, and the contribution of capital to output growth by three methods: ex-post, ex-ante and hybrid. Our implementation of the ex-ante method uses an estimate of the required rate of return for each country instead of the actual, average rate of return to calculate user costs and also employs the expected growth of asset prices rather than the actual growth. These estimates are derived from exactly the same data as for the ex-post method, ie without any extraneous data being employed. For estimating the contribution of capital to output growth, the ex-ante method uses ex-ante profit as the weight, while both the ex-post and the hybrid method use ex-post profit. We find that the three methods produce very similar results at the market economy level. But differences are much larger at the branch level, particularly between the ex-post and ex-ante methods.Capital, rate of return, ex post, ex ante

A Statistical Framework for the Analysis of Productivity and Sustainable Development

To analyse the consequences of the changing economic structure of the UK, we need aset of statistics broken down by industry that are consistent with the whole economymeasures available from the national accounts. The theory of growth accounting thenprovides a framework in which the contribution of each industry to the national economycan be measured and assessed. This paper identifies the obstacles currently facing aresearcher trying to implement this approach. It makes a number of recommendations forthe improvement of official statistics.National accounts, growth accounting, productivity