A Report prepared in February 2003.

Keywords: Growth & Innovation; Statistics;

Contents
Introduction
What is GDP?
Comparing GDP Through Time
Comparing GDP Between Countries: Purchasing Power Parity
How Satisfactory is the Adjustment?
Comparisons Through Time
Scaling PPP adjusted GDP
Ranking by GDP
Does GDP Measure Economic Welfare?
Alternative Measures to GDP

Notes

Introduction

GDP is used extensively in economic analysis and in the public economic discourse. More recently a particular version of GDP – per capita GDP measured in international purchasing power parity prices – has been used for international comparisons, and it has been argued that it is the relevant economic goal. Thus the target of ‘the top half of the OECD’ by some target date is to be evaluated by this measure.

This report is more cautious. It will argue that GDP is a part of a comprehensive system of economic analysis which enables systematic consideration of the economy at sectoral and industry level. Hence it is a valuable measure. However, it is inappropriate to use the indicator as an overall measure of the achievement of a society, or as its ultimate goal. For a number of reasons – which the report details – international measures of GDP suffer even further problems. Even so, comparing New Zealand’s per capita GDP measured in international purchasing power parity prices has so merit.

What is GDP?

Statistics New Zealand defines its Gross Domestic Product as ‘the total market value of goods and services produced in New Zealand, after deducting the costs of goods and services utilised in the process of production, but before deducting allowances for the consumption of fixed capital’.

There are three separate ways of looking at GDP. First, it is the aggregate net production of the economy. (The ‘net’ is to avoid double counting of inputs – including imports.) Second, it is the income that the production generates. Third, it is the disposal of the production, usually called ‘expenditure’. In principle each approach offers a different way of measuring GDP, but because all the production is disposed of, and because all the relevant income is generated from the net production, in principle the three measures yield exactly the same total. In practice there is measurement error, and so the actually measured totals can differ significantly (sometimes in percentage terms by more than the annual growth rate) because of measurement difficulties.

Note that the theoretical equality of the three measures only occurs when they are valued in the current prices. When other prices are used, there are theoretical as well as practical differences between the totals of the three measures.

GDP is the most prominent indicator derived from the System of National Accounts (SNA). As such, it is embedded in a comprehensive data base which attempts to characterise the main movements in the economy by statistical measures of income, production and expenditure at the aggregate, sectoral and industry level. Although this is not always evident in the popular discourse, economic analysis sees the various elements of the SNA interacting with each other – behaviourally as well as mathematically – and the GDP as a summary indicator of the interactions.

For many purposes another element of the SNA such as National Income (NI) would be a better aggregate outcome indicator. National Income is GDP less the consumption of fixed capital (depreciation), and reflects the income of the nationals (i.e of New Zealanders) rather than the income generated in New Zealand some of which goes to non-nationals. (NI also includes income New Zealanders earn overseas, which is included in other countries GDPs.) New Zealand National Income is a better measure of the true spending power of New Zealanders, that is (according to the definition proposed by John Hicks) the maximum amount they can spend and still have the same stock of assets at the end. It is still subject to the most of major criticisms of the inadequacy of GDP as a welfare indicator (below).[1]

GDP’s advantage is that it better reflects the underlying production basis on which the SNA is based, while the adjustments to derive NI are both conceptually problematic and subject to a larger error.

Comparing GDP Through Time

Because GDP is measured in market prices, and those prices change – especially given the tendency of the prices to generally rise (inflation) – a comparison of the ‘nominal’ GDP over time is not very useful. To facilitate a better comparison, the GDP at different points in time is valued in the same set of prices, usually the prices of the first year of the series.[2] This repriced GDP is sometimes called ‘GDP in constant prices’, or ‘real GDP’ (as opposed to nominal GDP), or ‘volume GDP’ (as opposed to value GDP). The ‘constant price’ name is the most technically correct, but a little clumsy. ‘Volume GDP’ is probably a better convenient term than ‘real GDP’, since the latter may imply to some that there is some GDP which is unreal.[3]

The repricing raises four problems, each of which also apply, to some (greater)degree, when international GDP comparisons are made.

First, not every item can be individually priced. One procedure is to obtain representative prices for some of the goods and services in a production or expenditure group, and to calculate a weighted increase of those prices, using that to deflate the change in the value of the production or expenditure. (It may be noted that international comparisons use far fewer commodities priced than national consumer price indexes.)

Second, new products arise and the quality of products change over time. There are a number of ways which statisticians allow for this, but ultimately one is left with the doubt that data comparisons through time are problematic because in the short run they dont properly allow for technology changes and in the long run they dont properly allow for new products.[4]

Third, some products cannot be priced as an output and have to be priced on an input basis. The public sector services are valued by the sum of their inputs (mainly labour). Where that happens, the procedure does not systematically allow for productivity changes although some countries make add hoc adjustments for believed changes in (labour) productivity. Additional capital goods (investment) are also, in effect, valued as inputs (so that an inefficient construction makes a higher contribution to GDP than a more efficient one which does the same job).

Fourth, while nominal GDP measured on the production side is exactly theoretically equal to nominal GDP measured on the expenditure side, the volume GDP measured from production and expenditure sides need not be theoretically equal. The divergence arises because of the impact of changes in relative prices between exports and imports (the terms of trade). Suppose export prices fall in a year relative to import prices, while the volume of exports remains exactly the same, and that all other prices remain the same. The constant-price production side estimate will not change between the two years. However there will be less volume imports (since the exports purchase less of them), less expenditure, so the constant-price expenditure side estimate will fall. Because New Zealand has experienced substantial terms of trades shifts, the distinction was important when wages were indexed to productivity changes. The expenditure side estimate of GDP was then called ‘effective GDP’, now defined in the SNA as ‘Real Gross Domestic Income’ (RGDI).

Comparing GDP Between Countries: Purchasing Power Parity

In principle the comparison between countries is exactly the same as the comparison over time: that is the same set of prices are applied to the production in each country.

Because the prices in different countries involve different currencies, in effect each product has its own exchange rate. Suppose the currency used for all product valuations was the international standard unit (ISU). Then for every product there would be a local currency price and an ISU price, and each ratio would be an exchange rate for each product. These exchange rates – or as they are known purchasing power parities (PPPs) – vary by product. For instance in 1998, the comparative price level most expensive New Zealand SNA group (Alcoholic Beverage, Tobacco and Narcotics) was 74 percent higher than the least expensive (Education).[5]

Before there was any of the detailed price comparisons (which exist for many, but not all, countries) the only available exchange rate was that between the internationally traded currencies. Converting GDP with the currency exchange rate was obviously wrong because changes in the exchange rates did not reflect underlying changes in prices.[6]

A textbook illustration of the notion of purchasing power parity is the McDonalds hamburger rate, which the London Economist publishes (it being easy for journalists to collect). The standard McDonalds hamburger has exactly the same content wherever it is sold. The Economist argues price for the hamburger reflects the average level of prices in the economy. But economies produce many more products than hamburgers, and the relativities between their prices and the hamburger is not constant, not least because case some of the inputs in a hamburger are subject to protection and subsidies – notably beef. Regrettably the McDonald’s exchange rate is given far more prominence than is justified.[7]

At the simplest level one might apply the prices of one country (as Australia) to another (New Zealand). The resulting measure might suggest the ‘Australian’ GDP was x percent greater than the ‘New Zealand’ GDP. Reversing the exercise, by applying ‘New Zealand’ prices to ‘Australian’ production might suggest that ‘Australian’ GDP was now y percent greater than the ‘New Zealand’ GDP. As a general rule ‘x’ will not equal ‘y’ so that different price purchasing power parity regimes give different relativities. This is no different in principle to what happens in price comparisons over different years (or the difference between the Paasche and Laspeyre price indexes). However the inter-country differences tend to be larger than the inter-time differences. Moreover, year data can be ordered through time. Country comparisons have no such general ordering, and the inclusion of a third country adds to the paradoxes. A different choice of an average set of international prices might lead to different relativities.

How Satisfactory is the Adjustment?

Deriving the international average prices is nor easy. There are technical answers, but they add a degree of error in that different answers may result in slightly different relativity.

There are three recognised weaknesses in the current procedures, which are also evident in the over-time comparisons, but to a lesser degree.
(1) It is difficult to get representative prices across economies. The McDonalds illustration makes it look misleadingly easy, but consider the complications of getting a price for something as basic as bread for a number of different countries given the variation in the style of breads. Housing is particularly difficult.
(2) The reliance on input measures for evaluating the public sector. In effect public sector workers with the same job specifications and qualifications are assumed to have the same productivity in all countries, an assumption which is clearly not true in the private sector.
(3) International comparisons of the price of capital investment products, are difficult.[8]

Recently, a further problem has been identified, although thus far the investigation has been preliminary. Products are priced differently depending on whether they are consumed or exported. Exports are priced at internationally traded prices while consumption is priced at (average) domestic traded prices. In a free-trade world the two would be the same (transport and distribution margins aside). However where there is protection there may be a substantial difference between the (average) export price and the (average) domestic price, and the PPP adjusted GDPs on the production and expenditure side will differ. In particular, the GDP of an economy whose exports face protection will be higher measured by the products it produces (the ‘production side’ estimate) than by the disposal of the products (the ‘expenditure side’ estimate). Conversely, an economy which protects its domestic industry but imports some of the protected product will have a higher expenditure side PPP.

Only the PPP adjusted expenditure side GDP is estimated. The implication is that those countries whose exports suffer strong discrimination will appear (relatively) lower than had the estimate been done on the production side. The exact meanings and implications are yet to be explored. It may be that the so-called PPP-adjusted GDP is more comparable with a PPP-RGDPI, that it is gives a measure of spending power rather than production.

There is a need to quantify the effect. The divergence for most OECD countries is likely to be small but in New Zealand’s case the difference may be in the order of 10 percent because of the high proportion of discriminated-against exports in GDP, and the high levels of discrimination. If so, half the gap between New Zealand’s PPP adjusted GDP and the mean may be explained by protection against New Zealand’s exports.

More generally, estimates of sectoral productivity based on the production side (the only practical way of doing this) will not sum to aggregate productivity based on PPP adjusted GDP derived from the expenditure side.

Comparisons Through Time

In principle the growth of PPP adjusted GDP ought to confirm to the growth of GDP based on the constant price series. As Table 1 suggests, there is a mismatch between the 1990 and 1998 figures.[9] Some 16 of the 23 economies experience an annual difference between the two estimates greater than 0.3%. Errors of this magnitude in a year tend to cause comment. Yet this was the average error for 8 years.

The implications could be some or all of:
(1) The 1990 PPP adjustments were wrong;
(2) The 1998 PPP adjustments were wrong;
(3) The constant price series are wrong;
(4) The expenditure side GDP on which the PPP adjusted series are estimated, has a different growth record to the production GDP figures on which the constant price figures are usually based;
(5) Revisions to methodology are important (as they certainly were between 1985 and 1990).
(6) It may reflect the ambiguity between GDP and RGDI. (When I used the RGDI growth rate for NZ instead of the GDP one the error difference was eliminated. However some of the country errors seem far larger than could be explained by a terms of trade effect.)

PPP adjusted GDPs are estimated at three year intervals, the previous rounds being 1980, 1985, 1990, 1993, 1996, and 1999. The next, due for release next year is for 2002. Other years may be interpolated or extrapolated using volume GDP growth rates. However this results of this section caution could be misleading. Additionally, the GDP (and population) data for individual years takes a little time to settle down because of revisions as new information comes in, so that extrapolation is more hazardous.

Scaling PPP adjusted GDP

Countries with bigger populations tend to have bigger GDPs, so it is usual to compare economies by per capita GDP. (Whether there should be some adjustment for the age distribution – children usually consume less than adults – is rarely considered.)

More recently there has been some attention to comparing the economies by labour force and by hours work. The resulting rankings are shown in Table 2. While the Netherlands is only 107 percent of the OECD average (of 27 economies – hourly data was not available for three OECD countries.) on a per capita basis, it is 145 percent on a per hour basis.[10]

Thus the US is behind Netherlands, Belgium, Norway, Italy and Ireland on a per hour basis.[11] Apparently part of US economic strength arises from Americans working longer hours. (The ‘apparently’ is necessary, because while the hours worked data comes from the OECD, it is not clear how well the individual countries are comparable and verified.)

New Zealanders work slightly more hours per capita than the OECD average, and so their average hourly productivity is slightly lower than the per capita one, measurement problems aside. The figure does not include commuting hours. If New Zealanders commuted an hour a day less than the OECD average, hourly productivity including commuting would be closer to 80 percent of the average.

More generally, adjusting for hours work (together with commuting hours were that possible) illustrates not only how fragile the relativities are, but that GDP by itself is inadequate insofar as it ignores the amount of accompanying leisure.

Ranking by GDP

The public rhetoric focuses upon New Zealand’s ranking and defines a goal in terms of ranking, rather as if it is a race. As in the Infometrics report prepared for NZTE, economists tend to work with the ratio of scaled GDPs, as in the second and fourth columns of Table 2, in contrast to the third and fifth columns. The technical reason is that a cardinal measure (such as a ratio) is far easier to work with than an ordinal measure (such as a ranking). In any case, there is a loss of information from reducing a cardinal to an ordinal measure, for ordinal measure (rankings) can be derived from cardinal measures (the ratio) but not the reverse.

Rankings can be very misleading. New Zealand lost only one place (to Ireland) between 1985 and 1999 on per capita GDP, but the relativity to average OECD fell by about 15 percent. On the other hand in the 1970s when New Zealand was growing as fast as the OECD, a number of countries growing fractionally faster passed it. There were few economies just behind New Zealand in 1985 and a lot in 1975. In racing parlance, in 1985 the economy could slow down to a walk but there was nobody near enough to pass it, whereas in 1975 New Zealand was catching up with the front runners, but others were catching up faster. That this can be misleading is evident from the Treasury growth studies which use rankings, and fail to pay sufficient attention to the poor performance in the late 1980s and early 1990s, because the ranking had not changed much.

Rankings hide bunching. The table shows five countries in the range 101 to 107 percent of the OECD average, all within measurement error of 104 percent. Slight errors may change rankings. In a recent paper The PPP Programme and the Uses of PPPs, the head of the program, Paul Schreyer cautioned that a 2 percent difference was within measurement error. Rankings give no indication of measurement error.

A further complication is that new member economies are being added to the OECD. Most are at the poorer end which means the OECD median and the mean are usually lower following the addition of new members (which also destabilises the data in past studies, and the public rhetoric).

In summary, the rankings are a poor way of characterising the situation New Zealand is in, has been in, and can be in. Relativities are better, but even they change as additional countries are added. Because of measurement errors, the relativities and rankings tend to jump around from data base to revised data base.

Does GDP Measure Economic Welfare?

The short answer to the question of whether GDP (or NI) is a good measure of economic welfare is that it is not. When the measure was systematically derived in the 1930s and 1940s, welfare was not a focus. The concern was with practical issues of how to determine employment and how to ‘pay for the war’. There is a theory which might be used to conclude that NI is a measure of welfare but it assumes the utilitarian theory that human welfare only increases by the increase in the goods and services transacted in the market.

While on occasions commentators – not always well versed in economics or the relevant theory – point out the inadequacies of GDP as a welfare measure, economists have long known of its deficiencies. In particular the measure omits those things which occur outside the market including most human interactions (including, has we have just seen, leisure), the interactions with the environment, and economic activity which occurs outside the market (such as most housework).[12] Not only are these probably more important, but it sometimes happens that GDP rises at the expense of the omissions.[13] GDP, which is typically measured in a short period of a year or a quarter is not an indicator of sustainability.[14] Much market activity is an input rather than an output in its own right. Examples include military spending, spending on crime justice and on health services, and the elimination of pollution. In each case it is possible to envisage a world where the spending was unnecessary and the nation was better off with a lower GDP: no military threat, without crime, without various health problems, and without pollution.

A further weakness is that GDP ignores the distribution of spending power (income). An economy with a highly unequal distribution of income may have the same GDP as one with a more egalitarian distribution. Yet we may want to judge the two to be quite different in welfare terms. Using GDP as a measure of welfare rests on so-called ‘Hume’s law’ that a dollar is a dollar is a dollar, where a dollar has the same value to a rich person as to a poor one.[15]

Awareness of these deficiencies has not led to their resolution. There have been various attempts to extend GDP to a wider measure, but typically they have proved neither compelling or robust. Among the difficulties have been how to provide ‘market’ prices for activities and transactions which do not occur in the market. Some efforts have also frequently lacked an understanding of the SNA framework out of which GDP is derived.

A recent development raises the even more serious possibility that in rich countries there is no indicator of material output which corelates well with human welfare. The utilitarian assumption that more material goods and services are associated with greater welfare and therefore GDP (or augmented GDP) is a measure of welfare, is an assumption, underpinned by little robust evidence utilising other independent assessments of welfare. Data reporting self-assessed happiness
– does not correlate with growth in GDP overtime (in fact the happiness level in countries where there is tracking remains constant despite rising per capita GDP);
– it correlates only weakly with relative income within countries (for instance marital status is a far stronger indicator of happiness than income);
– among the richest countries per capita GDP does not correlate with average happiness (New Zealand is third equal with the US, despite them being very differently ranked by GDP).

This last cross-national result suggests a possible interpretation. There is a correlation between GDP per capita and reported happiness for those countries with per capita GDPs lower than about 70 percent of New Zealand’s (although other variables are relevant too). This suggests that additional material product may contribute significantly to the welfare of people in poorer economies but that it is an asymptotic and other factors may be important for richer ones.

Alternative Measures to GDP

While researchers may want to explore alternatives to GDP as a measure of welfare, they need to pursue the same rigorous tests as those indicated for GDP. A measure needs to be a part of a comprehensive theoretical framework, which is practically useful, and has demonstrated the usefulness (i.e. been validated). One-off estimates are of little use: the need is for long run time series and cross national comparisons. No other measures meet these criteria.

Net Economic Welfare and Other Extensions

In 1972 two Yale economists, William Nordhaus and James Tobin, proposed a Measure of Economic Welfare (MEW) (now better known as ‘Net Economic Welfare’ (NEW)) in which they began with National Income from which they added the value of leisure time and the underground economy (including under-the-table services such as babysitting, but excluding illegal activities) and deducted environmental damages, the costs of education and health expenses which they judged ‘defensive’, and expenditure on personal security, police services, sanitation services, road maintenance, and the military. The resulting measure proved to have been growing steadily, but more slowly, than NI since 1929 in the US.

This triggered an plethora of associated measures. A popular one is the ‘Genuine Progress Index’ (GPI) proposed in 1995 which made many further adjustments, some of which involve judgements which experts might consider little more than opinions. The GPI for the US only goes back to 1950, but suggests an actual deterioration in recent decades.

However there is little agreement, no internationally comparable data, and no data series for New Zealand, for these new measures. So whatever their merits – they provide a useful base for a discussion of the value of GDP as an indicator of welfare – they are of little practical use.

The most promising development is that in 1993 the SNA set out a procedure for subsidiary tables which are slowly being developed on such activities as the environment, resources and housework, and which may ultimately lead to more general measure of sustainable economic activity, including non-market activity. But until these developments are completed – and even then they will address only some of the defects of GDP – the only measure that seems to meet the practical requirements of availability and rigour is GDP itself, although its use is limited by the caveats of its relevance to welfare discussed above.

Composite Indexes such as the Global Competitiveness Index

There is a practice of collecting together a number of indexes which are loosely related to economic performance and aggregating them. Into a composite index. Perhaps the best know of these is the Global Competitiveness Index, published by the Swiss-based World Economic Forum. Like the McDonalds PPP index, such composites are seized upon by journalists eager for ‘news’. The intellectual underpinnings are less compelling. The sub-indexes from which they are derived tend to be what is available and which suit the opinions of the index constructors, and the weightings of the components tend to be crude. Sometimes it is not even clear whether the variable should be positive or negative.[16]

Typically these indexes are not statistically validated, the opinions of the index constructors being the only justification that the index reflects some economic or social reality. There is no study which shows that the Global Competitiveness Index is usefully associated with economic growth. Even were there one, it’s status would be an input measure, not a(n output) measure of actual performance.

Human Development Index

The Human Development Index (HDI) has been proposed by the United Nations Development Agency, following a long debate in which economist Amartya Sen played a key role. It combines GDP per capita (PPP adjusted) with measures of educational achievement literacy and longevity, following Sen’s notion of the key notion of ‘capability’ which refers to the alternative functionings (‘life choices’) a person might have which indicate the freedom of choice a person has over their life. Material consumption is only a part of that totality, so health and education measures are included.

There are HDI tabulations for international comparisons, which discriminate among the poorer countries and sometimes dramatically change the placing of countries – most famously the Indian State of Karalla which is very poor but has world class longevity and literacy. However the measure is not very useful for rich countries, which tend to attain the maximum levels on each of the indicator the sub-components and so bunch together. Even so, the approach might be extended for them by incorporating measures of sustainability, quality of life and leisure. This has yet to be done.

Full Income

A useful measure, pioneered in Australia, has been ‘Full Income’ in which market income is adjusted for leisure and for the economic value of household assets (such as an owned home, consumer durables, and cars). However this measure is largely used to assess individual households rather than to assess aggregate welfare.[17]

An Index of Family Wealth

A recent proposal has been to use an ‘Index of Family Wealth’ as an indicator of welfare. [18] The indicator is rather unconvincing since it is based on a collection of some household items of families with 15 year old children, so it is neither comprehensive in coverage nor of the population. In any case it is a measure of household asset possession (ignoring financial wealth and debt), not of material product: it is a stock not a flow.

There been no attempt to validate the measure as relevant to welfare nor to fit it into a comprehensive theoretical framework. Another difficulty, evident in recent work by the Ministry of Social Development’s deprivation index, is that while a lack of items may be evidence of deprivation, at the other end of the scale there is a heterogeneity of possessions indicating high welfare. For instance some rich households may have a weekend bach, others may instead have a boat, and yet others neither but they may go regularly on overseas trips.

Does the Pursuit of GDP Undermine Wider Goals?

Much of the criticism of GDP as a measure of welfare is based upon an unease that its pursuit undermines wider social goals. There are some justified sources of such unease. At times, and in places even today, GDP (or perhaps just the unregulated market) growth has resulted in environmental degradation, increasing income inequality, plus other social ills such as rising crime. But while GDP growth has been associated with such detriments in the past and in places, in other times and places it has been associated with cleaning up the environment, less inequality, and reducing crime.

The unease with GDP is reinforced by the advocation of policies which are justified by the pursuit of higher GDP and yet which appear to damage other social goals. There is not the space to go through every argument and every instance, but a current New Zealand debate is revealing.

For various reasons every government intervenes, by spending and taxation, to change the composition of GDP. There is a theory which says that such interventions will reduce GDP (or, more tenuously, the growth of GDP). There is also an argument that such interventions may enhance GDP (or its growth). Advocates of the first argument have attempted to collect evidence to support their case (the same tests are also implicitly testing the second argument). Despite their persistence and ingenuity, to the scientific eye the advocates have quite failed to provide sound evidence.

I was surprised by this failure. While there may be beneficial effects on GDP growth from government spending, these tend to be long term, whereas the theory would predict the effects of taxation would be reasonably quick. Given the lack of convincing empirical evidence one concludes that any effect is so small as to be unmeasurable, and may be ignored within reasonable bounds.

But suppose there had been evidence that government interventions had depressed GDP. The interventions may still be justified if the differently composed – but lower – GDP was socially superior. It is not implausible that, given an effective and democratic political process, that the government interventions shift the economy in a more socially superior direction.

In fact nobody is a total supporter of GDP per capita as the ultimate social target. A ready means of lifting New Zealand into the top half of the GDP stakes would be to execute everyone over the age of 65. (Executing children too would take GDP per capita near Luxembourg levels.) A nation has higher goals than GDP per capita.

Of course the government should assess the effectiveness of its interventions, and ensure the burden of taxation is as light as is possible for given social goals, within those reasonable bounds. The evidence seems to be that New Zealand is comfortably inside the range, of, say, the tax burden or spending ratio to GDP.

Has GDP any Relevance to Welfare?

Given the above discussion has GDP any relevance to national objectives? The short answer is that a growth in GDP is an indicator of the ability of the community to increase its market production. This increase may result in greater community welfare insofar as
– it creates jobs for those who would be otherwise employed;
– increases Sen’s ‘capability’, indicating the freedom of choice a person has over their life. (Important instances of such enhancement could arise from spending on education and health, and the provision of community, cultural and recreational facilities);
– the resulting composition of GDP reflects national values. (In New Zealand’s case this would include more (private and public) spending on health services, education, on cultural and recreational services, and on environmental protection and enhancement.)

On the other hand, care has to be taken to ensure GDP growth does not result in social bads such as crime and social dislocation, and pollution and environmental destruction.

This approach s integral to the government’s ‘Growth and Innovation Framework’ and to its ‘Sustainable Development Strategy’.

Using GDP

The existence of GDP (or one of its associated measures such as NI) as a measure of economic performance is largely fait de mieux, there being no alternative which is as rigorously and comprehensively constructed, available over long periods, and for many countries. Perhaps one day there will be other measures – such as New Economic Welfare – which will have conceptual merits over GDP and which will be as readily available in comprehensive rigorous comparative data bases.

However there are positive aspects of the SNA cluster of measures (of which GDP is the most prominent) which is useful given a remit increasing the capacity of the New Zealand economy to produce in order for the nation to pursue its wider goals. That GDP is imbedded in an system of national accounts enhances its usefulness for those with concerns of sectors, exports and productivity.

However, GDP is not the ultimate national goal. The concerns captured by GDP are but one component which contributes to it. Sometimes other considerations may mean that a policy will depress GDP or inhibit its growth. It may be appropriate for agencies with primarily an economic remit, to draw the government’s attention to any depressing effects of the policy. But ultimately they will accept that in the government’s judgement the resulting composition of GDP may be socially superior. (Note, however, there is little evidence that the overall impact of interventions has been deleterious on GDP, so the effect of any particular one may not be great.)

Given the Government’s Growth and Innovation Framework specifically embraces the open economy – it will want to think about GDP and GDP growth in an international context. The best available readily measure would New Zealand’s PPP adjusted per capita GDP relative to some group of countries average (rather than the ranking between countries). The natural group of countries for comparison would be the OECD, although future additions to membership make comparisons over time complicated.

Moreover, as we have seen, PPP adjusted per capita GDP suffers from various measurement defects, including it is published for only every third year with a long publication lag (of almost three years). Given these difficulties what aggregate measure might we choose to assess the economic performance of the economy?

Choosing a Measure of Economic Performance

The first principle is that the measure should be a relativity not a ranking, that is New Zealand should be evaluated against some average performance of a group of countries. .

Given the need is for a robust and internationally accepted economic measure there is little available other than GDP measured in PPP prices. Where this is not immediately available it can be updated from the latest benchmark year by using volume GDP growth estimates. Ideally, and hopefully in the next few years practically, other related measures from the SNA system will become available. The most useful from the suite might be National Income measured in PPP prices. When a choice is offered between GDP on a production basis and GDP on an expenditure basis, it is likely that more weight should be given to the former, because of New Zealand’s lack of control over its terms of trade and the practice of international protection.

The current practice is to scale the GDP measure by population. It is recommended that this practice be continued until there are reliable estimates of hours worked. There is probably little merit in using the interim step of scaling by workers, because of differences in the treatment of part and full time workers.

What group of countries should the performance measure compare itself with? Here are some choices, noting that a major limitation on choice is that not all countries are included in the OECD exercise. The possible combinations are enormous, so only some obvious choices.

Countries

1. All the countries for which the OECD provides statistics. This consists of the 30 OECD countries, 8 candidate EU countries who may soon join the OECD, and 5 other countries Croatia, Israel, Macedonia, the Russian Federation and the Ukraine. In my view this group is too diverse, and in any case a number of them have standards of living and economic structures which are rather different from New Zealand’s.

2. All OECD countries. The difficulty here is that more countries are likely to be joining the OECD soon, so the group is not stable.

3. Pacific countries. This is a grouping which the PPP estimation process groups together: Australia, Canada, Israel, Japan, Korea, Mexico, New Zealand, the United States. (Israel is for convenience.)

4. A group of countries which are small, high income, and geographically isolated from the three main economic engines of the United States, the European core, and Japan. they might be Australia, Finland, Iceland, Ireland, Israel, New Zealand, Norway and possibly Denmark, Greece, and/or Portugal. The notion here is that size and isolation are two particular problems for New Zealand.

5. Australia, by itself, although comparing with a single country is likely to generate unnecessary rivalries and inappropriate comparisons of policies.

6. High middle income countries. The OECD partitions its 43 into three groups, and partitions again the middle group of countries into high middle income and low middle income country. New Zealand belongs to the later, which consists of 14 countries with Israel, Cyprus, New Zealand, Spain, Portugal, and Greece in order, at the top. The high middle country group (in order) is Iceland, Canada, Netherlands, Ireland, Austria, Japan, Belgium, Germany, Australia Sweden, Italy, United Kingdom. Finland and France, As the accompanying diagram shows, the division is not entirely arbitrary.

The challenge of New Zealand rejoining the High Middle Income Group would involve it growing about 1 percent p.a. faster in GDP per capita terms for a decade (on the current measure). Ultimately, that is probably the goal that New Zealand really seeks, although the path to the goal can be articulated in various ways.

Notes
[1] Note that NI (and, more generally, the National Accounts), cover only market assets, and do not allow for depletion of natural and environmental resources.
[2] More recently, the succeeding year GDP is valued in the prices of the preceding year. The longer series is constructed by chaining linking the overlapping year increases.
[3] The problem of measuring inventory change is not included here, because the inventory valuation adjustment issue which arises because prices change with the period of measurement, applies to nominal estimates also.
[4] In principle price indexes ought to be able to answer questions like: What amount of income in 1903 would enable a person to be on the same material standard of living as, say, the average wage in 2003. Because of the many new products over the hundred years it is difficult to even think about how to answer this.
[5] Not described here is the complicated system of weighting prices between countries.
[6] For instance between July 2001 and December 2003 there has been a 44 percent rise in the euro relative to the dollar. Yet it would be nonsense to infer there had been a similar change in the relative GDPs. If a country devalues by 19.45 percent, say, as New Zealand did in 1967, production did not fall overnight by 19.45 percent.
[7] The Economist has recently introduced a ‘Tall Latte’ PPP based on its price in Starbucks in 19 countries. The correlation coefficient between Starbucks latte and McDonald hamburgers was .79, suggesting either measure has some relationship with a true PPP but probably not a perfect one.
[8] For the 1985 PPP estimates, New Zealand was asked to provide a construction price for a two-up/two-down brick terraced house, while the price for the equivalent standard New Zealand bungalow was not requested. Because New Zealand builders were unfamiliar with such terraced houses their price was well out of line with typical construction prices in New Zealand. In the 1985 PPP adjusted GDP data for New Zealand, the volume of capital formation appears low relative to the volume of consumption. This instance has since been addressed, but it cannot be entirely avoided.
[9] The table is based on the 1990 and 1998 tabulations. Only 24 countries were reported in 1990. Germany was omitted because of the change in boundaries over the period. It is assumed that the average growth rates for the 23 are correct, since PPP adjusted data only gives relative growth rates.
[10] However, considerable caution is necessary in the use of the hour figures. There does not seem a lot of confidence that they are accurate/comparable.
[11] The exceptionally higher placing of Luxembourg probably reflect its rather special population (just as major cities tend to have higher per capita GDP than the rest of the economy) together with many of its workers commute from neighbouring countries. Its GNP relativity would be lower.
[12] A practical, rather than conceptual, omission is the unmeasured parts of the gray and black economies. We do not know their extent – attempts to measure it are unconvincing academic exercises – nor the extent the under-measurement differs from economy to economy or over time.
[13] When home childcare is replaced by paid childcare, GDP increases, even though there may be no effective change in total (market and non-market) economic activity.
[14] Resource depletion and environmental pollution may be a part of ‘Gross’ Domestic Product, but they are not deducted when ‘Net’ Income is derived, despite the activity being as unsustainable as capital depreciation.
[15] David Hume would be appalled to have his name associated with this as a welfare principle.
[16] A famous case, albeit from some years back, was a dispute as to whether the divorce rate was a positive in a national welfare index, indicative of a tolerant liberal society, or a negative indicative of marriage instability. (It is not difficult to see how the opinions of the index constructor would determine the way the divorce rate would be included.)
[17] Suzie Carson and I, using the New Zealand Household Survey data base, added to financial income an imputation for owner-occupied housing and found this ‘fuller income’ a better predictor of the expenditure items we were investigating. This suggests that ‘fuller income’ may be more relevant for household behaviour and welfare.
[18] It should be noted the article advocating the Index of Family Wealth makes some unfounded criticisms of the PPP measure which suggests the writer is not familiar with its methodology:
“The studies use rather outdated estimates of living costs. Other technical issues (such as the appropriateness of the basket of goods used in the measure) also raise concerns that PPP figures are not always reliable for making cross-country comparisons.”
The studies do not use ‘outdated estimates’: the 1998 estimates use 1998 prices. The concept of ‘living costs’ is not used by statistician and it is not clear what it means. What is meant by ‘the appropriateness of the basket of goods’ is also unclear, since the PPP measure covers all goods and services.

Various tables from the original report are not included

Go to top

Keywords: Growth & Innovation; Statistics;

Sources of Economic Growth in New Zealand: A Comparative Analysis is a paper attached to the latest IMF review of the New Zealand economy, prepared by Abdelhak Senhadji who was one of the IMF review team. It is on the IMF website After reviewing the record of New Zealand’s slow growth performance it presents a (reduced form) econometric equation which attempts to provide quantitative estimates of various influences on New Zealand’s poor performance. This paper reviews the study.

Notes: 1 . The paper is in a preliminary form and will be prepared for publication. Its writer saw an earlier version of this paper, and will it into consideration for revision. He reminded me, though, that sometimes I offer an impractical counsel of perfection.

2. The paper’s disclaimer that ‘it is important to stress that the results need to be interpreted with caution given that the relationship between the explanatory variable and GDP per capita growth in the estimated equations is not necessarily causal.’ While keeping the caveat in mind, I propose to proceed as though the causality is there.)

The Data Set

The data set is derived from a panel of 21 OECD countries for the period from 1971 to 2002, some 630 observations in all, the individual data items mainly coming from an OECD data base. How adequate is the data set?

But to begin with a methodological problem, which is not so much about the equation as about its use. The equation may find regularities across the panel of countries, but that does not mean it is necessarily useful for examining one or a subset of the data points in the panel. In particular the application to a single country may be inappropriate. My comments, which are about the relevance of the results to New Zealand, must be seen in this context.

The OECD Data Set

This data set is one of the best quality in the world, and I propose not to quarrel with it. It should, however be noted that very often National Accounting data for the December (calendar) year T is in fact for the March year T+1 in the case of New Zealand.

The Choice of Time Period

The time period beginning in 1971 reflects what is available for the OECD, but is unfortunate for New Zealand, because it experienced a major terms of trade structural shock in 1966 which the economy spent the next decade and more adjusting to. As I have said in another context, examining the New Zealand economy from 1971 is like studying the economy of Hiroshima from 1950.

Because of data base limitations, we cannot do much about the beginning date. But we need to be cautious about applying the resulting equation to New Zealand.

The Country Panel

The more I look at the OECD the more I am struck that there are two sorts of economic growth. While most grow at roughly the same ‘cruise’ rate as the rest, there are a handful which experience ‘turbo’ growth. Turbo growth is characterised by very rapid growth from a low level of per capita GDP, often doubling GDP in a decade. However, once the level of per capita output reaches that of the top countries, economic growth rates level at the cruise rate and so the economy joins the rest of the OECD. Examples include Germany in the 1950s, postwar Japan to 1990, Ireland and Spain in the 1990s, many East Asian economies including Korea in the 1980s and 1990s. Cruise growth is when the economy joins the top OECD bunch measured by GDP per capita (and where there maybe considerable doubts of exact rankings because of measurement problems). At this point the growth rates are similar and presumably so are the determinants of the growth rates.

Every country wants to instigate turbo growth, but the evidence is that once they join the throng at the top of the rich OECD this does not happen

The econometrics usually allows for this by the convergence effect (discussed below) but in my view that is inadequate. Turbo growth is fundamentally different from cruise growth. It is instructive that once the economy has joined the cruisers, the policies which seemed so effective under turbo conditions become as ineffective as they are for other cruisers. Turbo growth needs to be studies separately. My guess is that is usually depends upon the rapid absorption of underutilised resources (including underutilised skilled employed labour as well as unemployed labour) and the import of quality technologies (and often foreign capital).

The “New Zealand problem’ may be posited as to why New Zealand has not maintained a cruise growth rate in much of the post-war era, but has tended to be below it on average. My research shows that New Zealand has usually cruised at a similar rate to the rest, except on three or four occasions it stagnated for long enough to cause its relativity to other cruisers to change. I argue that these occassions are associated with a major shock to the external sector, either a fall in the terms of trade or a rise in the real exchange rate (both of which are equivalent to a fall in the profitability of the tradeable sector.) Whatever, the issue which arises out of the New Zealand problem is to compare New Zealand with other cruisers, not with the turbos. New Zealand’s turbo growth experience was from 1935 to 1945. The issue of turbos versus cruisers is a separate research project which does not particularly involve New Zealand. The New Zealand problem is why it was a slow cruiser.

Consequently, my preference would be to exclude from the panel countries Ireland, Japan, Korea and Spain (and possibly Norway because of the impact of oil finds on the economy). The easy prediction is that the ‘convergence effect’ will no longer be econometrically significant. The interesting question is whether any of the other coefficients will move.

Equation Specification

The equation consists of an independent variable change in (log) per capita GDP , which measures the GDP per person growth rat, with more than 13 independent variables discussed below.

Note that when the independent variable is a also change variable, say the change in (log) X, then the relationship can be integrated back and discussed as the level in (log) per capita GDP affected by the level of (log) X, so the regression coefficient is the elasticity between the variables (before logging). This is the form that I investigated. However the data in my equation was co-integrated order one, so I in effect estimated a similar ‘change’ equation.

Change in (log) per capita GDP: The difficulty with this variable is that the theory would suggest that rather than per person, it would be more appropriate to divide GDP by per worker, or better still, per hour worked, so that labour productivity is being measured (that being the relevant variable from the production function). The first is available in the OECD data base, but the available hours worked series are not reliable (and may not cover the whole period).

Additionally, the theory – confirmed by Steve Dowrick econometrically – says that (relative) population growth has an impact on GDP . Omitting this variable may cause population bias.

Now follows the independent variables.

(Log) GDP per capita in 1971: This is a levels variable. Its function is to test the convergence hypothesis, that is that poor economies grow faster until they catch up to the rich economies. I suggested earlier that this is a proxy for turbo performance, and it would be better to deal with that phenomenon separately.

Change in (log) employment: as mentioned, it may be theoretically more satisfactory to include this as a part of the dependent variable.

Change in (log) quantity of capital: while this is a theoretically correct variable to include (although some would think it should be included in a dependent variable which would better be measuring total factor productivity). However I have some concerns about its measurement.

To give a simple anecdote, when the price of oil rose in 1974 Japan quickly closed down most of its oil-fired smelters, which while not technologically obsolete were priced out of the market. However in the normal way capital is measured those smelters would have remained in the estimates of capital stock until they were slowly depreciated out. In the case of Japan such events may have be so small relative to the total as not to markedly effect aggregate capital stock, but in the case of New Zealand various events in the period were sufficient to affect the total. These include
– the dramatic collapse in the price of wool in the late 1960s which made parts of the capital invested in sheep farming obsolete;
– the removal of border protection in the 1980s and 1990s, which made parts of manufacturing capital obsolete;
– the fall in the price of oil in the mid 1980s which made obsolete parts of the gas-based petrochemical industry developed in the early 1980s.

Probably most of these early obsolesences had worked their way out by 2002, but the profile of available capital stock over the period does not the actual New Zealand measure.

It should be noted that the sum of the estimated coefficient on capital and the coefficient on employment come to between .32 and .35 in the four equations. That means that a 1 percent rise in employment and capital would raise output by only .35 percent at most.

Inflation: The inflation variables (explained below) are measured by the CPI. I am never sure the of relevance of this measure, since the CPI is not a measure of production inflation, it being greatly affected by import prices. (The path of the New Zealand CPI shows considerable divergence from that of GDEF, the GDP deflator.) Since a GDEF is available in the OECD data base,, and it is the relevant production side variable, why not use that?

The equation uses two inflation variables, because it believes there is a curvilinear relationship between economic growth and inflation. While I am not antagonistic to that hypothesis, it is perhaps unfortunate the way it was tested (even aside from the wrong price measure). It assumed the turning point was an inflation rate of 3 percent p.a. and then had a linear function on both sides, instead of putting in a quadratic function. For the record, the regression estimates suggest that increase of inflation from 0 to 3 percent p.a. would add .6 to .8 percent to annual GDP growth.

However because of the asymmetry, inflation at 10 percent p.a. would give as much growth as inflation at 0 percent p.a. I am not sure I believe that, but even so it suggests that the 1 to 3 percent inflation target is wrong and a better one might be 2 to 6 percent p.a., with a ‘midpoint’ of 3 percent p.a.

I worry whether it makes sense to combine the high inflation era of the 1970s and early 1980s with the low inflation era which followed. It is possible that a dummy variable splitting the period into two would do as well or better. In some respects for a small country may be concerned more with the relative inflation rate to other OECD economies.

Savings Ratio: I have not spent enough time on the OECD measure of the national savings ratio to comment on this independent variable. Since it includes public savings, and assuming any Ricardo effect is negligible, an implication is that the New Zealand government running a 7 percent of GDP budget surplus seems to be adding about .2 percent p.a. growth to GDP. (I will not comment on the implication of the US fiscal position.)

Change in (log) Relative Unit Labour Costs: Again I am not sure how robust this measure is (since if we dont have a good track on hours worked, how can we have one on the hourly wage?). The regression estimate suggests that a ten percent annual wage hike reduces GDP growth by about .5 percentage points, a figure which many unionists would find attractive.

Change in (log) Terms of Trade: This variable is theoretically justified and significant. However its effect seems very small, for it says that a 10 percent reduction in the terms of trade will reduce the level of GDP by about .2 percent. In the case of New Zealand that is almost certainly too small. (I have independently estimated the impact is closer to 6.2 percent).

The trouble may be that there is no lag structure in the model, for a terms of trade shock may take effect over a number of years (and indeed initially be perverse in the case of livestock slaughter). It is also possible that the effect is non-linear. In particular the New Zealand economy has probably accommodated to the steady but annually small decline in the terms of trade for meat and some dairy products. It is the big shocks which have upset it.

The estimation included ‘two dummy variables for the oil shocks in the 1970s’ but not one for the reverse oil shock of 1985. The estimates are not given so the magnitude cannot be commented upon. They probably need to be thought of as system shocks rather than terms of trade ones, since oil price changes already appear in the terms of trade. (This might be the reason for omitting the 1985 shock.) In some ways an oil price shock to the world is analogous to the wool price shock to New Zealand.

If the terms of trade are a relevant variable, then so too is the real exchange rate, since there are different aspects of the profitability of the export sector. (They are different because the real exchange rate includes the price of non-tradeables, which is not in the terms of trade, and because it treats export and import prices together rather than in ratio.) I have used for the real exchange rate the ratio of GDEF (GDP deflator) divided by the harmonic average of the price of exports and imports, which is available from the OECD data base. In the New Zealand case the effect of the rising real exchange rate seems important (indeed to my astonishment, more important than the terms of trade in the long run). (See External Impacts and the NZ Economic Growth Rate. ) It will be returned to below, both in the discussion of the New Zealand dummy and in the discussion on mis-specification.

It is also appropriate to put on record an issue which has begun to worry me (and others). The OECD terms of trade applies to merchandise exports and imports only. How are we to allow for the rising proportion of services in international trade?

Share of Government Consumption in GDP: The trouble with this variable is that even though it omits transfers (which seems wise given the complicated but differing ways that they impact in different countries), different countries have different conventions in the measurement of government consumption. In particular, New Zealand levies its GST (a Value Added Tax) on all government consumption in exactly the same rate as it levies it on private consumption. This may have the effect of artificially raising the New Zealand ratio by 12.5 percent or about 2.5 percentage points of GDP relative to many other jurisdictions. However the effect of the ratio seems small. (It is unclear what the units of measurement are, but if they are a pure ratio, a country with a 1 percent of GDP higher spending ratio would have its growth rate reduced by .00002 percent p.a., if it a percent – as hinted in Table 2 – it would be .02 percent, which makes some contribution to explaining the dummy and distance effects described below).

Tax Variables: Two tax variables are included – the highest marginal individual and corporate tax rates. Again depending upon the way each variable is measured, their effect may be very small.

Openness: This variable is measured by the ration of exports to GDP. While this does not directly affect New Zealand, a number of countries are entrepot centres – importing and exporting the same products. That seems to me to be quite a different activity to what happens in NZ. Either the variable should be adjusted for re-exporting, or perhaps treated as non-linear.

There is also a deeper problem here which I have not seen addressed. On this measure America would appear to be a relatively closed economy. But each of the states of the US would be relatively open. On the other hand, individual states of the European Union are treated as separate observations, which gives the impression that Europe is more open that the US. How to deal with this aggregation problem?

(The point here is not to challenge the notion of openness leading to growth, although the effect may be curvilinear, in the sense that a more open economy is likely to grow faster – at least if it is small. The issue is how to measure openness.)

I am surprised that openness has been seen to lower New Zealand’s GDP growth rate. By the mid 1990s the export to GDP ratio was about 32 percent, above the (weighted) OECD average of 19.5 percent (and the US of 12.5 percent).

Other variables: the oil shock variables have already been mentioned. There is also a time trend and an adjustment for the business cycle.

There is no indication whether the time trend is econometrically significant. Presumably it refers to a belief that there is a secular slowing in the average cruise growth rate of all the rich OECD. However some would argue that while that may have happened in the 1970s and 1980s there was some growth acceleration in the 1990s.

The report mentions that ‘all variables which are business cycle sensitive have been pre-filtered with the HP filter to remove business cycle frequencies.’ Unfortunately in New Zealand there is no single business cycle frequency., the length of the cycle varying between two and a bit and almost seven years.

The New Zealand Dummy: In two of the four equations a dummy variable for New Zealand is added. It suggests that New Zealand tends to grow slower than the average OECD, after adjusting for all these other effects, by about .5 per cent p.a. However a similar dummy is not included for any other country. This leads to the next variable, but as explained below, we are on dangerous methodological grounds.

Distance: Table 4 it suggests that Australia and the US are distant but Canada is not. I suspect there should be an adjustment for tho countries which are themselves ‘economic centres’.

There are two methodological concerns with this distance variable. The first is that it is not at all clear how distance affects the growth of GDP. It is easy enough to give an explanation, as to why the costs of distance may lower the level of GDP, but the connection to growth is much less obvious and needs to be explained.

Second, the way that the distance variable is introduced is uncomfortable. The econometrics found an anomaly of New Zealand’s behaviour, via the use of a dummy variable (but it did not check whether any other country was also anomalous). It then, in effect replaced the dummy variable by a pseudo-dummy which has many of the characteristics of a dummy variable since it is constant throughout the period impacts, largely on a single country New Zealand (but also Australia), and which seems mis-specified. However no other possible variables are tested – I would predict that the proportion of the population who play rugby is likely to be about as equally effective. But having identified one pseudo-dummy it is easy enough to identify others. (It would also be appropriate to redefine the varibale so that large economies are defined as close to themselves.)

In practice the difference could be due to measurement difficulties (recall the problem of the measurement of government spending) or an omitted variable. In the latter case a candidate must be the real exchange rate, because it is difficult to explain the course of the New Zealand economy from the late 1980s without it.

What seems to be happening here is that there may be an omitted variable, but the distance variable is far from proven. We turn now to specification problems.

Specification Problems

Omitted variables

The theory of econometric mis-specification concludes that omitting a relevant variable is likely to bias the remaining parameter estimates, while including an irrelevant variable will not. Omission, then, can be a very serious problem.

Among the potentially important variables that appear to be omitted are:

1. Relative population growth;
2 The real exchange rate;
and possibly a
3. A business cycle or capacity utilisation variable (although there may be no suitable candidate in the OECD data base and the filtering procedure used may be the best available, if markedly inferior).

Mis-specified variables

Among the improvements that might be made to the variable specifications are:

4. Scale GDP by employment or hours worked instead of population.
5. Use GDEF (the GDP deflator) as the measure of inflation, and put it in as a quadratic form so that the ‘bottom’ is not predetermined.
6. It may be appropriate to include lagged variables.

Additionally there are other ideal improvements, but there are no suitable data series.

Observations

As already mentioned the turbo economies should be dropped from the panel (or at the very least other regression runs should be done without them).

And always the counsel of perfection is to obtain longer data series, if that is possible.

Estimation

The estimation procedure seems to be ordinary least squares. It covers variables which are co-integrated to degree zero and one. The likely effect of this mixture may be that the standard errors of the regression coefficients are biassed down, so they seem more precise (and significant) than they are.

I suspect this is so because so many of the parameters are tiny, but significant.

Conclusion

This is written from the perspective that the original report represents progress, and that by subjecting it to rigorous review, with positive suggestions for improvement, further progress can be made.

Even so, the methodological question of the usefulness of the equation to understanding New Zealand remains. In particular it seems to me that it sheds little light on the following questions:

1. Why did the New Zealand growth rate slow down at the end of the 1980s so that for five successive years there was a reduction in the GDP per capita?

2. Why was there a recovery of the growth rate to more normal levels in the mid 1990s.

Go to top