Select Committee on Economic Affairs Written Evidence

Memorandum by Dr David Maddison, Senior Lecturer in Environmental Economics, University College London



  1.  Efforts to reduce greenhouse gas emissions are perceived to be very costly. Little is known, however, about people's preferences for a particular climate or their willingness to pay to avoid negative impacts of climate change. Research work on the economic consequences of climate change has generally focused on changes in productivity in sectors such as agriculture, energy and tourism or on the costs of sea level rise. The impact of climate change on households has been largely ignored although I believe that it is here that the most profound impacts of climate change will be felt. In this note I shall attempt to address the following questions: Do households have preferences for particular types of climate and if so why? How do households reveal their preferences for particular types of climate? Will households necessarily be damaged by climate change or will some gain and if so who will gain and by how much?

  2.  Climate is an important input to many household activities. Climate influences our health and determines our heating and cooling requirements, clothing and nutritional needs. Climate also fashions our leisure activities and particular types of climate are known to promote a psychological sense of well-being. Climate also has an indirect effect on households' welfare in that particular types of climate support fauna and flora over which households may have preferences. It would be of no surprise to find that households living in climatically different regions are likely to purchase different patterns of goods even if they face the same incomes and the same prices: it is to compensate for or alternatively take advantage of particular types of climate. Furthermore otherwise identical households living in different climatic zones are likely to enjoy different levels of welfare. Finally there can be no presumption that changes in climate will necessarily be detrimental to households. It may be more helpful to think of climate change moving household closer to or further away from an optimal climate.

  3.  In order to determine how good or bad climate change is monetary estimates of willingness to pay for climate amenities are required. A number of methods have employed in this respect including: Hedonic analysis; Migration analysis; Household Production Function approach; Hypothetical Equivalence Scales; and Happiness studies. Before explaining these valuation techniques in more detail and discussing the evidence that they yield on the question of to what extent do households value the climate it is worth pointing out that all of these methodologies depend on non-testable assumptions. Some of these assumptions are more plausible than others especially in the context of valuing climate amenities. There are also significant data problems which researchers using these techniques have struggled to overcome. It would therefore be foolish to place too much faith in the results of any one study. Only when multiple applications of the same technique in different contexts point in the same direction, and when different methodologies produce similar results can one feel more confident about drawing conclusions. I think that we are nearing that point.


  4.  If at the same time as being free to adjust patterns of demand individuals are also freely able to select from differentiated localities then climate itself becomes a choice variable. The tendency will be for the costs and benefits associated with particular climates to become capitalised into property prices and wages. Thus, across different locations there must generally exist both compensating wage and house price differentials and in such cases the value of marginal changes in climate can be discerned from hedonic house and wage price regressions. As an example, the observation that all else being equal property prices are higher and wage rates lower in areas characterised by lower rainfall would be taken as evidence that households view rainfall as a disamenity. By examining the increase in house prices and the reduction in wage rates associated with a one millimetre reduction in rainfall one could derive the amenity value of rainfall to households.

  5.  The main advantage of using the hedonic technique to deduce the value of climate variables is that since one is in effect using current day analogues for future climate change it can be presumed that long-run cost minimising adaptation has already occurred. Apart from its strong theoretical underpinnings and familiarity it is in this sense that the hedonic technique possesses particular appeal.

  6.  Unfortunately the hedonic technique has some drawbacks when used in this context. Barriers to the movement of households exist as would prevent them from bidding up the price of houses in locations with desired climates. This problem is exacerbated because climate varies only over significant distances. A further problem is that at any moment in time labour and housing markets are likely to be in disequilibrium. Many other factors determine the desirability of a location and climate is unlikely to be the most important determinant of locational choice. One therefore has to be concerned about the risk of mistakenly attributing variations in house prices to climate when in reality they are best attributed to another variable not included in the model.

  7.  Notwithstanding these difficulties Maddison and Bigano (2003) use the hedonic technique to analyse the amenity value of the climate of Italy. They find that labour incomes net of housing costs are significantly higher in areas with high July temperatures, high January rainfall and cloud cover and interpret this as evidence of a compensating differential. Households are shown to dislike high levels of precipitation in January and high temperatures in July. The latter results seem especially plausible since frequently debilitating July temperatures are normal for Italy and this is clearly alarming in that climate change is predicted to increase July temperatures in Italy. The most interesting finding however is that whereas the Milanese would be willing to pay a significant amount to increase the fraction of clear skies in both January and July, people living in other locations would not. Here there is a direct correspondence between one of the most unusual features of the Italian climate—the persistent fogs in the Po Valley—and the results of the analysis. By contrast the remainder of Italy enjoys relatively clear skies. The willingness to pay for a one unit change in climate variables is given in Annex 1. The correct interpretation of these figures is for example that a household would be willing to pay 648,000 Lira to avoid a 1(ºC) increase in July temperatures. Note also that the willingness to pay for a one unit change in climate variables differs with location. This is because the underlying climate of Milan and Rome is different and it provides evidence in favour of the existence of an "optimal" climate. These figures could be combined with actual changes in climate to compute an overall estimate of the impact of climate change on Italian households.

  8.  Rehdanz and Maddison (2005) use the hedonic approach to measure the amenity value of climate in Germany. The evidence suggests that households in Germany are compensated for climate amenities mainly through hedonic housing markets rather than labour markets. Houses are more expensive in areas with higher January temperatures which the authors interpret as evidence that households are willing to pay for an increase in January temperatures. Households are also willing to pay for a reduction in precipitation in January and a reduction in July temperatures. The results are very similar to those obtained from Italy although obviously the climate of Italy is more varied than that of Germany and somewhat warmer. The distinguishing feature of this study is that the authors have an abundance of high-resolution data and control for differences in the level of over one hundred amenities. The authors show that the same results pertain of sub-regions of Germany. There is in this study therefore little chance that the significance of the climate variables is due to confounding. A number of other studies exist for the United States.


  9.  Hedonic studies focus on equilibrium outcomes whilst migration studies focus on the process of equilibration. Migration decisions are made on the basis of differences in wage rates, housing costs, employment possibilities. Do regions with more desirable climate ceteris paribus experience net inward migration? How much extra income in the form of higher wages and lower property prices is necessary to encourage a household to stay in an area with an unpleasant climate? Migration studies attempting to explain the influx or outflux of individuals from particular regions can also be used to make inferences about the amenity value of climate.

  10.  Cragg and Kahn (1999) consider migration patterns between different states of the US. They consider the propensity of individuals to move between states as a function of the characteristics of those states namely wage rates, house prices and amongst several other things climate variables. The results indicate that individuals appear to be paying thousands of dollars to enjoy preferred climates. More specifically the authors find that individuals are attracted by high wintertime temperatures, low summertime temperatures, sunshine and low humidity. Interestingly the authors are able separately to estimate the willingness to pay for climate variables for individuals at different stages of the life cycle. More elderly people have far stronger preferences for climate which obviously accords with expectation.

  11.  There are many more studies of migration in which climate has been included despite not being the main focus of interest. In virtually all of these studies climate variables have been found to be highly significant (see Cushing, 1987 for a summary). This approach is an interesting adjunct to the hedonic approach although Cragg and Kahn demonstrate that the results can differ between the two approaches. It shares some of the weaknesses of the hedonic approach namely the assumption that individuals are willing to move large differences in order to realise the net advantages afforded by different locations and the risk of confounding.


  12.  As household expenditures increase household expenditure shares typically change. The share of household expenditure spent on some commodities declines whereas the expenditure share accounted for by other goods tends to increase. Assuming that the number of children imposes fixed costs on the household how much money would a family with children have to be given before it exhibited the same pattern of expenditure shares as a household without any children? In the Household Production Function approach the difference in income would be interpreted as the cost of the children and could be inferred by comparing the expenditure patterns of households with and without children. In fact such an approach is regularly used in economics to calculate the needs of households with differing composition and the extension to climate variables is straightforward. Analysing household expenditure patterns how much more income (if any) would a household living in a cold climate require before it resembled a household living in a warmer climate in terms of expenditure shares? One might imagine that a household living in a colder climate would experience greater fixed costs in terms of its need for heating and warm clothes and would therefore need extra income before its expenditure shares resembled those of a household inhabiting warmer climate. These extra costs represent the amenity value of a warm climate.

  13.  In order to undertake a Household Production Function study for climate variables it is necessary to possess data on expenditures drawn from households living in climatically different zones. It is also necessary to control for all the other factors that might explain why households exhibit different commodity expenditure shares such as different prices, incomes and demographic variables. The advantage of the approach is that it enables the researcher to understand why climate is of value to the household in the sense of what commodity groups are sensitive to differences in climate. Unlike the hedonic and migration approach it does not require one to assume that households are willing to move substantial distances to eliminate the net benefits of different locations. The weakness of the approach is that it assumes that the only role played by climate is supplanting the need for marketed commodities such as heating and warm clothing.

  14.  Using a sophisticated version of the Household Production Function approach Maddison (2003) analyses broad commodity consumption patterns for 88 different countries by reference to prices, incomes, climate and other demographic differences. The climate variables that he included (average temperature, temperature range and temperature deviations and similarly for precipitation) significantly contributed to explaining the variation in demand especially for food and drink, clothing and footwear, and miscellaneous goods. Surprisingly the demand for energy and housing were not affected. He then calculates the change in the cost of living imposed by a particular climate change scenario provided by the UKMO associated with carbon dioxide doubling.

  15.  According to the simulations all of Northern Europe would benefit from limited climate change at least insofar as amenity values are concerned. These gains are particularly pronounced for the United Kingdom and Ireland. Italy on the other hand appears largely unaffected by climate change. Indeed, among the European countries represented in the data set only Greece is adversely affected by the hypothesised 2.5 ºC increase in annually averaged global temperatures. Turning to Asia, a completely different picture emerges with the majority of countries losing from the predicted climate change scenario. The highly populated countries of India and Pakistan are particularly hard hit. All the African countries represented in the data set appear to lose from predicted global climate change. In North America, the United States is largely unaffected by climate change. Further north Canada enjoys a reduction in the cost of living. Mexico on the other hand suffers a large increase in the cost of living.

  16.  Although this study is wide in its ambit a major defect is the fact that each country is assumed to represent a homogenous climatic zone. This is not unreasonable for a small country like a Caribbean island but wholly implausible for a country like the United States. Maddison attempts to overcome this problem by using a climate index that is weighted according to the population of the main cities in each country but this is no substitute for possessing micro-economic data.


  17.  In the Hypothetical Equivalence Scales approach a sample of individuals are asked whether they would describe an income of $X as good, bad or neither good not bad for someone in their particular circumstances. Amount $X is varied across the sample and the results analysed using regression analysis to determine what factors the respondents implicitly believe mean that their household requires higher incomes to reach any arbitrarily defined level of welfare. Individuals' answers seem to reflect the size and composition of their household. For example, individuals with a larger number of children tend to declare that they need higher incomes to reach the same level of welfare.

  18.  The underlying assumption of this technique of course is that individuals share a common understanding of what constitutes a "good" and "bad" standard of living. Evidence suggests that this is not a wholly robust assumption. Nonetheless this technique avoids the need to collect the difficult to obtain data on expenditure patterns required for the Household Production Function Study. It also deals with situations in which climate affects welfare in ways other than through reallocation of expenditure.

  19.  Friijters and Van Praag (2001) present hypothetical equivalence scales for Russian households. Amongst other things they find that implicitly individuals take account of climate variables in their verbal assessment of particular income levels. The results indicate that Russians strongly prefer warmer winters. Put another way, individuals living in areas of Russia enjoying warmer winters were happy to describe the same level of income as "good" that someone living in an area characterised by colder winters would describe as "poor". The values identified by the Friijters and Van Praag study suggest that the gains to Russia from higher temperatures could be very significant.


  20.  Although it may seem bizarre at first blush psychologists have long invited individuals to state how happy they are on a 1-5 scale. Recently economists such as Professor Richard Layard have started to use such studies to examine whether growth makes people happy and whether inflation and unemployment make individuals unhappy. Analyses of the economic determinants of happiness now appear with regularity in leading academic economics journals such as the American Economic Review, the Review of Economics and Statistics and the Economic Journal. In these studies happiness, welfare and utility are taken as being synonymous with one another.

  21.  Although it appears very difficult to explain cross-country differences in average happiness scores, Rehdanz and Maddison (2005) use cross-country data on self proclaimed happiness to analyse preferences for climate. Happiness is clearly potentially affected by a large number of economic variables, demographic variables, cultural variables, civil liberties as well as environmental variables like climate. Despite including a sizeable number of variables in their attempts to explain international differences in happiness scores only per capita income and climate are significant. It appears that low winter temperatures and high summer temperatures make people unhappy—precisely what was found in the hedonic studies for Italy and Germany.

  22.  Rehdanz and Maddison use their results to simulate the change in real GDP per capita necessary to hold happiness (or welfare) at its current levels in the face of predicted changes in climate. Countries in high latitudes like Canada, Norway, Finland, Sweden, Iceland, Denmark, Great Britain and Ireland gain from climate change. Countries for which precipitation is expected to increase in previously dry months like Peru, Venezuela or India are also likely to gain from limited climate change. The full results are shown in Annex 2 and are of course dependent upon climate model predictions regarding the expected pattern of climate change. The proper interpretation of these figures is for example that an increase in GDP per capita of $138.58 would compensate Argentinians for the kind of climate change predicted by 2039 under the business as usual emission scenario. A negative sign as for example for Armenia means that the country would benefit from climate change.


  23.  A large number of methodologies have now been used to measure the amenity value of climate in monetary terms. Despite differences in geographical context, the quality of the data and the plausibility of the underlying assumptions most studies indicate that climate is rather important to household welfare. It is nonetheless difficult to say whether different methodologies produce similar results not least because they characterise climate in a different way (eg average temperature versus temperature deviations versus January and July averages).

  24.  A number of the studies described in this note merely uncover household preferences for climate and present their results in terms of willingness to pay per unit change. But being able to determine households' preferences for climate change is only part of the story. To obtain the overall welfare impact it is necessary to combine these preferences with estimates of the extent of climate change. Some of these approaches determine the amenity value of climate to today's households. Future households will be richer and face different prices for goods and commodities. This will affect the perceived impact of climate change. It is an interesting question whether future households will be more or less impacted by climate change. It is also interesting to speculate whether poorer households are likely to be more affected by climate change because the commodities on which they tend to spend the majority of their income are those that can be supplanted by climate. Valuation studies offer the prospect of resolving these interesting and important questions.

  25.  On the basis of the research described in this note I do not know if the impact of climate change on global amenity values will be positive or negative. In any case the amenity values presented in this paper are only part of the overall impact of climate change: there are the changes in productive activities like agriculture and forestry as well as the effects of sea level rise and the loss of biodiversity. I do, however, feel secure enough to assert that the impact of climate change will redistribute welfare between countries and that some countries will gain from limited climate change. Two very different studies both suggest that high latitude countries will enjoy a significant increase in amenity values from climate change whereas low latitude countries will lose.

  26.  There is abundant scope for more elaborate attempts to estimate the amenity value of climate to households here in the UK as elsewhere. For example, the data used to estimate amenity values used by all of these studies was collected for another purpose and is generally aggregated over politically defined regions. Much more accurate results could be obtained by using higher resolution data collected over climatically homogenous zones. The valuation techniques described in this paper have been widely used to value other environmental goods but there are very few applications to climate. It would be quite possible to conduct a high quality hedonic house price study for the United Kingdom as well as a household production function study. But there is resistance to valuing the impact of climate change in monetary terms and also to the idea that climate change may be not detrimental to all countries. More than anything however there is simply limited awareness of the possibilities afforded by such techniques amongst researchers and those who fund climate change research.

28 February 2005


  Cragg, MI and Kahn, ME, 1997. New Estimates of Climate Demand: Evidence from Location Choice. Journal of Urban Economics, 42:261-284.

  Cushing, BJ, 1987. A Note on Specification of Climate Variables in Models of Population Migration. Journal of Regional Science, 27:641-649.

  Frijters, P and Van Praag, BMS, 1998. The Effects of Climate on Welfare and Wellbeing in Russia. Climatic Change, 39:61-81.

  Maddison, D, 2003. The Amenity Value of Climate: The Household Production Function Approach Resource and Energy Economics, 25:155-175.

  Maddison, D and Bigano, A, 2003. The Amenity Value of the Italian Climate. Journal of Environmental Economics and Management, 45:319-332.

  Rehdanz, K and Maddison, D, 2005. Climate and Happiness. Ecological Economics, 52: 111-125.

  Rehdanz, K and Maddison, D, 2005. The Amenity Value of Climate to Households in Germany. Submitted to the Journal of Environmental Economics and Management.

Annex 1

January Temperatures (ºC)-193 -386
July Temperatures (ºC)-648** -711**
January Precipitation (mm)  -42*   -33**
July Precipitation (mm)  -43   -58
January Clear Skies (%)317* -443
July Clear Skies (%)620** 110
Source: Maddison and Bigano (2003). Note that ** means significant at the 1 per cent level and * means significant at the 5 per cent level of confidence.

Annex 2


CountryYear 203 9 Year 206 9
Bosnia—Hercegovina158.89 276.68
Czechoslovakia89.95 151.70
Dom Republic65.02103.48
Great Britain-26.87 -53.56
New Zealand38.5459.10
Northern Ireland17.68 34.86
Puerto Rico37.8660.37
South Africa158.04272.01
South Korea-95.27-160.09

  Source: Rehdanz and Maddison (2005).

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