Issues in the Hidden Economy-A Survey* MICHAEL CARTER

Australian National University, Canberra, ACT 2600

This paper discusses a number of questions concerning the so- called hidden economy. What b the hidden economy? How big is it? Is it really growing? D m it matter? What should we do about it? The paper b not an exhaustive survey of the literature on the hidden economy. Its objective b more modest- namely topresent an overview of the state of rtxarch, identifv the major themes and issues and provide a framework for further work.

Spurred on by the growing resistance to ever increasing tax burdens, economists and other social scientists have recently been encouraged to re- examine their definitions and measurements of economic activity. Research has spawned a burgeoning literature on the hidden (alias underground, informal, irregular, twilight, black, cash, subterranean) economy. It has fostered the belief that the hidden economy is large and growing. But how big? Is it really growing? What is the hidden economy anyway? Does it matter? What should we do about it? These questions form the basis of this paper.

Much of the economic literature on the hidden economy revolves around techniques of measurement. This emphasis on measurement is accordingly reflected in this paper but attention is also paid to definition, causes and consequences. Section I considers the definition of the hidden economy while Section I1 discusses some of the reasons which have been suggested for growth in the hidden economy. Section I11 surveys the variety

I gratefully acknowledge the influence of the constructive comments and suggestions of my colleagues Fred Gruen and Rodney Maddock. the editors of the Economic Record and an anonymous referee. Jennifer Anderssen and Eva Klug provided helpful research assistance. Naturally I assume full responsibility for any errors or deficiences in the resulting product.

Editors’ note: This paper was commissioned by the Survey Editor.

of techniques which have been adopted to measure its size and growth. Concern about the hidden economy arises primarily because unrecorded activity escapes taxation and regulation. There are other consequences of a growing hidden sector which, although they have received less attention, may be more deleterious. These issues are addressed in Section IV. Finally Section V summarizes the major conclusions. The paper does not purport to be an exhaustive survey of the.literature on the hidden economy. Its objective is more modest - namely to present an overview of the state of research, identify the major themes and issues and provide a framework for further work.

I What is the Hidden Economy? The hidden economy means different things to

different people. Definitions are almost as numerous as the multitude of names which have been applied to the phenomenon. Some definitions focus on tax losses, others emphasize shortcomings in the traditional measurement of GDP, while others would encompass a much broader range of economic activities.

In its broadest sense, the hidden economy encompasses all unmeasured economic activity. Feige (1979, p. 6) defines the hidden economy as including those economic activities which ‘go unreported or are unmeasured by the society’s current techniques for monitoring economic activity’. This definition extends beyond currently accepted definitions of GDP. It would embrace those activities which are excluded from GDP by

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210 THE ECONOMIC RECORD SEPT.

convention (for example household production) as well as those activities which elude the measurement process.

Most economists have adopted a narrower view of the hidden economy which stays within a conventionally accepted accounting framework. For example, Tanzi (1980, p. 428) defines the hidden economy as ‘GNP that, because of unreporting and/or underreporting, is not measured by official statistics’. Similarly, Britain’s Central Statistical Office def ies the hidden economy as ‘the economic activity generating factor incomes which cannot be estimated from the regular statistical sources used to compile the income measure of gross domestic product’ (Macafee 1980, p. 81).

The distinction here can be clarified by considering the twin problems of bias and measurement (or sampling) error which confront any measurement process. Measurement begins with an idealized concept of some quantity which it is desired to measure. In an attempt to obtain an operational definition which can be implemented, the compass of the quantity to be measured is restricted somewhat. The difference between the idealized objective and the operational measure constitutes bias. Further errors are introduced in the process of actually conducting the measurement. T h e constitute sampling or measurement errors.

Total Output

Ridden

Eeonomr h o m y

Error

W FIGURE 1

Components of Total Economic Activity

In the measurement of aggregate output, certain forms of economic activity are excluded from the operational definition of GDP (bias). Other forms of economic activity, while included defhtionally, fail to be adequately recorded because of the inadequacy of the measuring tools (measurement error). The distinction is illustrated in Figure 1. Total economic activity is represented by the whole

circle. Only a portion of this economic activity is measured and appears in estimates of aggregate economic activity; the remainder constitutes the hidden economy. This in turn can be subdivided into two components - bias and measurement error. The borderline between bias and measure- ment error is depicted as a dashed line to indicate its uncertain nature. It is not always clear whether a given deficiency is a problem of bias or measurement error. For example, is informal production involving barter excluded from GDP because GDP is restricted to monetary exchange (bias) or because the economy lacks suitable means to 8ssess its value (measurement error)?

The hidden economy then can be divided into two conaptual categories. Economic activity which is excluded from GDP by definition (bias). We might call this the informal economy. Economic activity which is excluded from GDP through measurement error. We might call this the under- ground economy.

By this definition the informal economy comprises those economic activities for which no attempt is made at measurement. Examples include most household production, cooperative activities such as babysitting clubs, neighbourhood organizations and sports and recreation clubs. Burns (1975) and Gershuny (1979) have drawn attention to the increasing proportion of production which takes placc within the household and in the informal economy, this transformation being stimulated by the availability of household capital equipment - the ‘self-service economy’. Some economists, for example Eisner (1978), Kendrick (1979) and Hill (1979), have attempted to incorporate household activity into a comprehensive measure of economic activity.

The underground economy involves those economic activities which are embraced by current definitions of measurable economic activity but which are not captured by current measurement techniques. Frequently their escape from measurement results from deliberate concealment to avoid taxation or regulation. Examples include unreported earnings, perks, fringe benefits and other payments in kind, and the production of illegal goods and services. There is a large body of literature which focuses on the role of perks, pilferage and other hidden aspects of the employment relationship and their role in industrial relations (Henry, 1978, Mars and Nicod, 1981, and the Outer Circle Policy Unit, 1978).

It is debatable whether all illegal activity should be considered as belonging to the underground

1984 HIDDEN ECONOMY 21 1

economy. Should the production and distribution of illicit drugs be regarded as productive economic activity? Some would argue that GDP should encompass the production of all goods and services for which there is a market demand. This clearly includes the production and distribution of illegal drugs. Yet this position seems inconsistent with the expenditure of considerable resources in the attempt to impede the same activity. It is therefore unclear whether illegal activity should be regarded as belonging to the underground economy or being outside the purview of economic activity altogether. There is a subset of illegal activities which does not result in the production of new goods and services but rather redistributes existing income and wealth. Examples include burglary, robbery, extortion and fraud. Such unproductive illegal activities should not be included in any measure of aggregate output.

The division of the hidden economy into the informal and underground economies provides a useful conceptual categorization. However, it must be emphasized that the distinction between the informal and underground economies is illdefmed. Many of the activities which are excluded from GDP by definition (informal) are excluded only because of the difficulty of measurement and not on the basis of any theoretical distinction. Most economists have confined their attention strictly to the underground economy thus taking the conventional definitions of economic activity as given (as, for example. in the definitions of Tanzi and the CSO above). Other writers, for example Burns (1975), Gershuny (1979) and economists such as Eisner (1978) and Kendrick (1979), have devoted primary attention to the informal economy. A definition such as that by Fiege quoted above would embrace both components of the hidden economy. This Seems to be a desirable starting point. In coming to grips with the full extent of the hidden economy, it is inadequate to concentrate purely on measurement error.

To clarify the issue, consider the example of a householder who is discouraged from employing a painting contractor because of the higher costs which are imposed through taxation and regulation. The householder can either employ a painter for cash on which tax will not be paid or undertake the painting task personally. In the former case the activity is transferred to the underground economy while in the latter case it takes place in the informal economy. In both cases the economic activity escapes measurement and GDP is correspondingly lowered. In both cases the proximate cause of the reduction in measured GDP

is the higher costs induced by taxation and regulation. Confining attention to the underground economy (as defined above) will not uncover the full extent of the hidden economy.

II Causes of the Hidden Economy One reason for the concentration of most

economists on the underground component of the hidden sector is the almost universal belief that the growth in the hidden economy is a direct result of higher and higher taxes and the proliferation of economic regulation. Despite the frequency with which this has been asserted by economists, journalists and politicians, virtually no evidence has ever been offered to support this proposition (Feige. 1980). In a recent paper Frey and Weck (1 983) assemble

some evidence which should caution against naive views of the causes of the hidden economy. If taxes and government restrictions are the main causes of growth in the underground economy (Tanzi, 1980. pp. 428-30), we might expect countries in which taxes are relatively high or government restrictions rather more pervasive to have larger than average underground economies. Frey and Weck (1983) attempt to test this proposition by ranking 17 OECD countries on two criteria: the share of taxes (including social security contributions) in GNP of taxation, and the proportion of public administrators in the total workforce. Combining these two measures in a variety of ways, Belgium, Denmark, the Netherlands and Sweden consistently rank highly and therefore would be expected to have rather large underground economies. Conversely, Italy, Ireland, Japan, Spain and Switzerland have low ranks and would be expected to have small shadow economies. These results conflict sharply with many preconceptions. In particular, Italy is often cited as an economy in which the underground economy flourishes. Though crude, these comparisons should caution against the belief that the hidden economy is merely a response to high taxation and other restrictions.

It seems appropriate to distinguish betwecn the incentive and the opportunity for hidden activity. High tax rates and pervasive regulation supply the incentive for hidden activity. The opportunity for evading taxes and regulations depends upon other factors such as the level of development, social structures, public acceptance of compliance-‘tax morality’ in Frey and Weck’s terminology. The conventional assumption that taxes are the primary cause of the hidden economy can be saved by

212 THE ECONOMIC RECORD SEPT.

arguing that those countries in which there is a high incentive to evade (Belgium, Denmark, the Netherlands and Sweden) have a low opportunity. Conversely, economies with large hidden sectors such as Italy and Spain have ample scope for evasion even though the incentive for evasion is quite weak.

This apparent ascendancy of opportunity over incentive is tenuous. It is possible to turn the conventional proposition on its head and argue that taxes are low in countries where the underground economy is large. It might be that tax rates are low in Italy precisely because Italy has a flourishing hidden economy, whereas taxation is an effective means of raising revenue in Sweden because most economic activity is overt and measured. Italy makes do with a smaller public sector because it has inherited a large hidden sector.

No one seriously doubts that taxation is an important factor in motivating the hidden economy. But these inter-country comparisons suggest that the relationship between taxation and hidden activity is not simple and unidirectional. They suggest that other factors also play a role in promoting hidden activity.

In reporting on a household survey in Chicago, Ferman and Berndt (1981) comment on some of the factors promoting hidden economic activity:

There are a variety of reasons for working in the irregular economy, and in most cases there is more than one factor involved. The economic benefits of participation are very important, but coupled with this may bethe fact that opportunities for participation in the irregular economy surpass those available in the regular sector. Certain characteristics of irregular activities other than their economic benefits, such as the relative freedom and autonomy and flexibility they offer, are also important [pp. 35-61.

For some, irregular work is a way of surviving without submitting to the routine of a regular job, a way to develop new skills leading to a change in occupation; or an informal market testing ground for a fledgling business venture. These and other considerations often combine to set the incentive for participation . . . A belief in self sufficiency and the virtue of work can be as strong a motivation as a desire to beat the system [pp. 38-91.

It reasonably can be assumed that a similar panoply of incentives operates in Australia.

Participation in the hidden economy appears to be widespread. In their household survey, Ferman

and Berndt (1981) found that the participants in the hidden economy came from all walks of life. They included full- and part-time employees, unemployed and people not in the labour force. Participants could not be characterized by race, ethnic origin, social group or occupation. They included people dependent on transfer payments and others who were financially independent.

Arguments that the irregular economy is the particular domain of any category based on distinctions of occupation, income level, employment status, social class, sex, age or race are at present no more than unfounded speculation . . .

In our research we found little evidence to support popular contentions that the poor, the unemployed, the unskilled and the disadvantaged are actually gainfully employed in the irregular economy [Ferman and Bandt, 1981, pp. 39-40].

This assessment is supported by the work of Dilnot and Morns (1981) who subjected the returns from a British household survey to detailed scrutiny. They found evidence of participation in underground activity in all occupational and employment status groups. The self-employed were more than twice as likely to be engaged in underground activity than employees; part-time employees had hi&a participation rates than full- time employees. From the occupational perspective, administrative and technical skilled workers are more heavily involved than the unskilled. There is little distinction between skilled and semi-skilled workers. Occupational variation was less significant than employment status. Identification of the characteristics of the participants in the underground economy along the lines of Dilnot and Morris (1981) is a promising avenue for further research in Australia.

Although surveys provide some insight into the motives for participation in the hidden economy, these remain one of the most important and least understood issues. Economists have been too ready to attribute the apparent growth of the hidden economy to the ravages of taxation or other restrictions. No one would deny the importance of taxation in encouraging underground economic activity; focusing on that factor alone is unlikely to produce either complete diagnosis or appropriate prescription.

III Measuring the Hidden Economy While direct measurement of the unmeasurable

1984 HIDDEN ECONOMY 213

is obviously impossible, hidden activity leaves traces in measured activity through which it can be assessed indirectly. The methods that have been used show considerable ingenuity and creativity. O'Higgins (1980) provides a useful taxonomy. The primary distinction is between macro measures based on aggregate data and micro measures which rely on individual data collected, for example, from surveys. A number of different measures have been attempted in each category. In the following discussion, two or three approaches in each category are discussed in detail to illustrate the methodology. Other similar methods which have been reported are mentioned for completeness and problems which are common to the category as a whole are discussed.

The following discussion is confined to attempts which have been directed primarily towards measuring the underground economy rather than the informal economy and to this extent they represent only partial measures of the hidden economy. For measurement estimates of the informal economy, see for example Eisner (1978), Kendrick (1979). and Snooks (1983).

Macro Measures With the increasing use of demand deposits and

the proliferation of credit cards and other financial instruments, the value of currency in circulation might be expected to decrease relative to the value of demand deposits. In fact, however. the ratio of currency to demand deposits has risen in many countries in recent years. It was the attempt by Gutmann (1977) to explain this fact which is credited with stimulating the interest of economists in the underground economy.

underground economic transactions are conducted in cash rather than with cheques. The increasing proportion of currency in the money supply was required to support a growing underground economy. Assuming that the ratio of currency to demand deposits in 193841 was normal, that any excess of the current ratio over that of 193841 was due to underground activity, and that the velocity of circulation of currency was the same in both the regular and underground sectors, Gutmann estimated the size of the underground economy in United States in 1976 at 10 per cent of GNP. Adapting this approach to Australia, the Commend Bank of Australia (1980) estimated the size of the underground economy in 1978-79 at 10.7 per cent of GDP.

Gutmann began with the assumption that,

Problems with this approach include the following: it is very sensitive to the choice of base year; the assumption that the ratio of currency to economic activity in the underground economy is identical to that in the formal economy is fundamental; and there are many other factors which influence the holding of cash (Cagan, 1958).

In an attempt to cope with the latter problem, Tand (1980) estimated an explicit demand for currency equation in which the ratio of currency to total money (MZ) is a function of the tax rate, the interest rate on time deposits. the share of wages and salaries in personal income and real per capita income. Tanzi estimated the size of the underground economy in the US at 8-12 per cent of GNP. A similar study by Evans and Renehan (undated) for Australia (using the ratio of currency to demand deposits) obtained comparable esti- mates. Norman (1982). allowing for the effect of inflation on the demand for currency, estimated the size of the underground economy in Australia in 1981-82 at 13.4 per cent of GDP.

A serious objection to the suggested inter- pretation of these studies is the absence of any increase in per capita currency holdings. which ceterispuribus would be expected if there had been a significant increase in the percentage of cash transactions. There has been a marked increase in the ratio of currency to demand deposits in Australia in recent years, but this has been brought about by a reduction in demand deposits rather than an increase in currency holdings. Figure 2 depicts currency holdings and demand deposits for Australia. Adjusted for inflation, currency per capita is now lower than it was 30 years ago. Expressed in 1981 dollars, per capita holdings of currency fell from $497 in 1950 to 3309 in 1966 returning to $454 in 1974. During the late seventies, which is commonly regarded as the heyday of the underground economy, currency holdings per capita remained almost static in real terms. On the other hand, demand deposits per capita adjusted for inflation have declined by almost 50 per cent over the 30-year period. It is this which accounts for the increase in the ratio of currency to demand deposits. The hidden economy interpretation of the increase in the ratio of currency to demand deposits implicitly assumes that the factors which led to economizing in the use of demand deposits should have an equivalent impact on the use of currency. In particular it isassumed that the interest elasticity of demand for currency is equal to the interest elasticity of demand deposits. The validity of this assumption remains to be tested. The size of

214 THE ECONOMIC RECORD SEPT.

currency holdings in Australia does not necessarily provide evidence of a rapid growth in the cash economy.

Currency and Demand Deposits Per Capita ($1981)

Following IMng Fisher, Feige (1979) argues that the total value of monetary transactions in the economy is a good measure of aggregate economic activity. The total value of transactions can be estimated from bank records coupled with estimates of the turnover rates of currency. He suggests that any increase in the ratio of transactions to measured GNP is due to the growth of the underground economy. Taking 1939 as the base year, Feige estimates the size of the under- ground economy in the US in 1978 at 33 per cent of GNP. In latter work Feige (1980) has modified his approach to take account of some perceived deficiences and arrives at a revised estimate of 27 per cent of GNP in 1979.

Feige’s method can be illustrated by starting from Fisher’s simple identity

M V = PT where M = the quantity of money (currency + demand deposits),

V = transactions velocity, P = the price level, and T = volume of transactions.

The relationship between the volume of transactions and the total income in the economy

will depend upon factors such as the relationship between intermediate and final transactions, the volume of transfers and the extent of financial transactions. This relationship can be represented

PT = kPY.

as:

Combining these two equations, we have M V = k P Y

which can be rewritten as PY = (V/k)M.

This equation reveals the essence of Feige’s transactions approach. Using information on M, k and V he estimates total nominal income, PY. This exceeds reported income (GNP); the difference being an estimate of the hidden economy.

In effect, Feige turns the demand for money equation on its head. He regards money supply and velocity as exogenous and uses these to estimate the level of income. To estimate the transactions velocity V, he considers currency and demand deposits separately. Estimates of the turnover of demand deposits can be obtained from bank records. Estimating the turnover of currency is more difficult. Feige relies on some estimates of the effective physical life of currency. As for the ratio of transactions to income k . Feige treats this as a constant. Assuming that the hidden economy was nonexistent in 1939, he uses that year’s observed income to calculate a value for k which is then applied to all subsequent years.

Feige’s estimates are critically dependent upon the assumed constancy of k and on his estimates of the turnover rate of currency. The constancy of k seems highly implausible. There have been a multitude of social and economic changes since 1939 which would be expected to increase k-the massive growth of the tax and transfer system and the development of financial markets to mention just two. Feige’s attribution of the observed increase in income velocity to the hidden economy is also inconsistent with the marked decrease in real per capita demand deposits recorded in Figure 2. The distinction between Gutmann’s and Feige’s approaches to measuring the hidden economy is the latter’s belief that the underground economy is transacted in cheques as much as in cash. Molefsky (1982) has shown Feige’s estimates imply that cash accounted for only 37 per cent of underground transactions. The rest must have been conducted by cheque. This amounts to 14 per cent of all cheque transactions.

1984 HIDDEN ECONOMY 215

Denison (1982) has argued that a significant growth in the underground economy would be accompanied by a decline in recorded employment. Wages and salaries comprise such a large proportion of GDP that under-estimation of the latter implies some underestimation of the former. Since wages and salaries and employment are derived from the same data source, they can be expected to share any bias. If wage and salaries are underestimated, employment similarly must be understated. Therefore, Denison argues, any growth in the underground economy must be reflected in a decline in employment. However employment rates in the United States, whether aggregate or age specific, have not declined in recent years. This is inconsistent with the supposed rapid growth in the underground economy.

It is possible to counter Denison’s employment figures by arguing that employment rates would have grown had it not been for the underground economy. There is no convincing way in which we can postulate a ‘normal’ trend for employment rates. However the stability of recorded employment certainly poses some problems for the proponents of a rapidly growing hidden economy.

Denison’s argument receives support in a recent Australian study. Fisher (1982) examined labour statistics in Australia to assess the scope for under- reporting. While he identified some specific opportunities for under-reporting, he concluded that there is ‘no major discrepancy consistent with anecdotal reporting of informal labour market transactions’ (p. 31).

In the United Kingdom the size and behaviour of the statistical discrepancy (expenditure-income) has been used as evidence of a growing hidden economy (O’Higgins, 1980). although th is approach is now regarded with considerable scepticism (O’Higgins. 1982). Fisher (1983) analyzed each component of aggregate expenditure in Australia to assess its scope for under-recording which he then aggregated to provide an estimate of unrecorded expenditures. The increase in the use of larger denomination bank notes relative to smaller denominations has also been advanced as evidence of the growth of the hidden economy. It is not clear that the movement towards larger denominations exceeds that which might be expected as an adjustment to inflation (O’Higgins,

Essentially macro measures of the underground economy attempt to measure the change over some period of time. To infer an absolute size requires the specification of some ‘standard’ such as a base

1980. pp. 17-21).

year in which the underground economy is assumed to be nonexistent. Gutmann and Feige chose the late 1930s as the period when the (US) economy was entirely overt. This is clearly quite arbitrary and it has been shown that estimates of this type are very sensitive to the choice of base year. In the United Kingdom the currency ratio declined in the late 1960s and 1970s. By appropriate choice of the base year it is possible to ‘show’ that the hidden economy in the United Kingdom is now negative (O’Higgins, 1980, p. 16, Dilnot and Morris, 1971, p. 167).

A second difficulty with these measures involves the attribution of causation. Some relationship is postulated arbitrarily, and the difference between the observed outcome and the postulated outcome is attributed to the hidden economy. In Gutmann’s work, for example, it is assumed that the currency to demand deposit ratio would have been constant but for the growth of the hidden economy. For Feige it is the ratio of transactions to income which is assumed constant. The divergence from the postulated constant is attributed to the hidden economy. More sophisticated models, such as that of Tanzi (1981). gosome way towards meeting this challenge. However, all the macro approaches attribute the unexplained residual to the hidden economy.

Illegal activity creates problems for measures of the hidden economy which are based on inferences from the use of currency. Such measures inevitably incorporate illegal activity, some or all of which should rightly be excluded from measures of aggregate output. A special problem undermining monetary studiesof theunited Statesis the fact that US currency circulates internationally. The OECD (1981) argues that this explains rapid growth of currencylmoney ratios in the US, a pattern which has not been matched in other countries.

Micro Measures Tax authorities are in a position to make an

assessment of tax evasion on the basis of audits which they conduct. A major study was made by the US Internal Revenue Service (Tanzi. 1980). The IRS estimated that between 4.4 per cent and 5.8 per cent of legal income was unreported (Tanzi, 1980, Table 1). Not surprisingly this was heavily concentrated amongst the self-employed who accounted for 44 per cent of unreported income.

Norman (1982) analyzed the list of selected income tax evaders published by the Australian Commissioner of Taxation for the income year 1978-79. He found that the average income of the

216 THE ECONOMIC RECORD SEPT.

detected evaders was more than twice that of the population average and that the mean understatement of income was approximately 50 per cent. Speculating that the detected evaders were a representative sample and that 7 per cent of the workforce were involved in tax evasion, Norman estimated that total unreported income amounted to $8.44 billion or 8.3 per cent of GDP. This estimate is significantly higher than that revealed by household surveys discussed in the next d o n , which raises some doubt about how representative the Commissioner’s ‘honours list’ is.

Using data from the British Family Expenditure Survey, O’Higgins (1980) found that the self- employed consistently spent a higher proportion of their reported income than employees. Since it is widely acknowledged that the self-employed have much greater opportunities for tax evasion, this discrepancy can be used as a measure of tax evasion. On this basis, O’Higgins estimates that income tax evasion by the self-employed in Britain amounted to 18 per cent of their income of 2 per cent of national income.

This interpretation, however, demands some care. Selfaployed incomes are considerably more variable than wages and salaries. Therefore we should expea the expenditure ratio of the self- employed to vary with their income and consequently with the state of the economy. In other words, we are really interested in the ratio of permanent expenditure to permanent income. Household expenditure surveys inevitably incorporate transitory components. The observed ratios will be sensitive to economic conditions at the time of the survey.

These reservations are supported by corresponding Australian data. Australia has conducted only two household expenditure surveys (1974-75 and 1975-76); another is due to be conducted in 1984. The relevant data are summarized in Table 1. The first survey reveals a higher expenditure ratio for the self-employed whereas in the second survey the self-employed report spending a lower proportion of their income than employees. These two surveys differ not only in date but also in coverage. The 1974 survey is confined to the capital cities and thus excludes farmers who comprise a large percentage of the self-employed. It is also worth noting that the average income of the self-employed is lower than employees; the opposite is the case in the British data.

The real puzzle posed by these data is why the self-employed in Australia do not report higher expenditure ratios given the fact that they clearly have much better opportunities for evasion. Is it perhaps that they under-report both income and expenditure? Or is it the case that they do not under-report income in the household surveys? They may have more profitable savings oppor- tunities than other households. Another possibility is that employee also understate incomes and parti- cularly gross incomes.

Dilnot and Morris (1981) have made an extensive analysis of individual records from the British Family Expenditure Survey. After making various adjustments to these data, they identified all house- holds whose expenditure exceeded income by a cer- tain threshold. These households were then systematically examined to filter out those for

TABLE I

Australian Household Expenditure Ratios

-~ ~

1974-7s 1975-76

Self Self Employees Employed Employees Employed

Average weekly expenditure 221.53 247.24 245.18 218.33 Average weekly income 236.38 232.32 266.88 250.62 Ratio of expenditure

to income 0.94 1.06 0.92 0.87

Source: ABS Homhold Expenditure Survey 1974-75, Bulletin 8, Table 1, and Household Erpcndirure Survey 1975-76. Bulletin 2, Table 1 1 .

1984 HIDDEN ECONOMY 217

whom reasons other than underground activity might explain the discrepancy. By this process they selected two subsamples whose responses provided evidence of unreported income. The lower bound sample differed from the upper bound sample in that it resulted from the application of a more stringent filter. Approximately 9.6 per cent of households surveyed qualified for the lower bound sample whereas the upper bound sample comprised 14.8 per cent of households. Extrapolating these percentages to the total population and multiplying by the average discrepancy between income and expenditure, they obtained an estimate of the hidden economy. Their results are summarized in Table 2.

The Dilnot and Morris study is an innovative use of survey data which also yields some interesting information on the characteristics of participants in the hidden economy.

Labour force surveys have also been used to investigate involvement in the underground economy. For example, Aldren (1981) looks at the incidence of moonlighting. Fisher (1982) discusses the extent to which the various Australian labour force surveys may incorporate activity in the hidden economy. Time use surveys, see for example Gershuny and Thomas (1980, 1983), and Krupinski and Mackenzie (1979). constitute another rich source of data which have not yet been used to assess the extent of hidden activity.

Although they avoid some of the difficulties of aggregate measures, micro measures of the hidden economy have problems of their own. First, such data are very difficult and costly to collect. Conducting a welldesigned survey is an expensive and time-consuming business which may be difficult to justify merely on the grounds of investigating the hidden economy. On the other hand, surveys which are conducted with other purposes in mind, such as tax enforcement, may give an incomplete or inconsistent picture.

A second difficulty is a direct consequence of the first: the cost of undertaking micro studies means that they are likely to be irregular and to lack inter- temporal consistency. This makes it difficult if not impossible to chart the development of the hidden economy over time. One of the great advantages of the aggregate methods surveyed in the previous section is that the data on which they rely are available for long periods of time and hence it is relatively straightforward to compile time series. This is not possible at present from micro studies. This shortcoming of micro surveys could be overstated. The time series compiled from macro measures are only as meaningful as the underlying estimates.

The third difficulty faced by micro measures involves sample bias, response bias and deliberate deception. Surveys like the household expenditure survey and time use studies are voluntary. It is possible that the sample who agree to participate are unrepresentative of the population as a whole. Participants in the hidden economy may be significantly less willing to collaborate than those whose economic activity is regular and official. When they do take part in a survey, those engaged in hidden activity may be inclined to conceal some or all of that activity, wittingly or unwittingly. It is difficult to estimate the extent of this bias.

Conclusion There is abundant anecdotal evidence regarding

the black economy. Attempts to give more precise quantitative measures to this phenomenon have yielded an impressive range of estimates: anywhere from 2 to 33 per cent of GDP. Almost invariably it is the aggregate measures which lie at the higher end of this range. A closer analysis of the data and methods suggests that these estimates should be treated with generous scepticism. On the other hand, it is likely that the bias in the micro measures lies in the opposite direction. For the reasons

TABLE 2

Lower and Upper Bounds for the Hidden Economy in Great Britain, 1977

Lower Bound Upper Bound

Proportion of FES sample 9.6Qo 14.8% Average discrepancy between income and expenditure

(pounds per week) 31 30 Implied proportion of GNP 2.3% 3.0%

Source: Dilnot and Morris (1981, Table 2).

218 THE ECONOMIC RECORD SEP?’.

already discussed (such as incompleteness, sample bias and deception), micro measures probably tend to under-estimate the size of the underground economy. The two different approaches lend themselves to interpretation as upper and lower bounds respectively.

IV Consequences of the Hidden Economy The major stimulus for recent interest in the

hidden economy is the belief that it is detrimental to social welfare. However this concern can be tempered by some reservations regarding the actual size of the hidden sector and the knowledge that the hidden economy may provide some offsetting benefits. This section discusses several of the undesirable consequences which have been canvased in the literature and then mentions some of the benefits which might flow from the existence of an unregulated sector.

Economic Disinformation Economic analysis and policy rely on official data

which reflect only a portion of total activity in the economy. If the relationship behueen the measured and hidden components of economic activity is constant, major economic indicators such as the growth rate, the level of unemployment and the inflation rate wi l l not be distorted by the omission of the hidden economy from the economic data base. However, if the hidden economy is growing relative to the formal economy, major economic indicators such as the growth rate of GDP. the rate of inflation, the unemployment rate and the growth rate of productivity will be biased unfavourably. This is the opposite of the effect recognized by development economists in which the apparent dramatic growth experienced by countries beginning the process of development is in part a statistical illusion, reflecting the incorporation into the measured economy of previously unmeasured economic activity. These deficiencts in economic measurements are

not merely a matter of professional pride. Economic statistics are used not only to assess performance but also as an essential guide to policy. If the guide is significantly in error, so also might the policy. Feige (1980. 1981) regards the growth of the hidden economy as the root cause of the economic malaise which has afflicted industrialized countries during the previous decade. He argues that the period of 1%169 was the ‘golden age of economics’. During this period there was a constant relationship between the measured and the hidden

sectors so that economic policy was based on an undistorted view of economic activity. It appeared that economists had attained a high level of control over the economy.

But this achievement was shortlived. The economic consensus evaporated with the unexpected and unexplained simultaneous occurrence of unemployment and inflation. Feige’s explanation is simply that the disease is a mirage, a statistical illusion based on the fact that our economic data base applies to a dwindling com- ponent of the total economy. This he calls the unobserved income hypothesis which he describes as follows:

Most simply stated, the UIH suggests that systematic biases. unwittingly introduced into our official data, have fundamentally distorted our perceptions of economic realities. A distorted information system leads rational individuals and well-intentional policy-makers to undertake actions that transform initial statistical illusions into real economic maladies Feige, 1981, p. 205).

In other words the flow of resources from the measured to the unmeasured sector seriously distorts our picture of economic performance. In responding to inaccurate economic statistics, governments and other decision makers implement policies which are inappropriate to the true state of the economy. These policies in turn do real damage to economic performance. Simultaneously, they promote the transfer of resources to the hidden economy, magnifying the inadequacies of con- ventional statistics and promoting more inappro- priate policies.

Government Finance The hidden economy affects both sides of the

government budget. On the revenue side, one of the main incentives for the underground economy is the avoidance or evasion of taxation. This increases the relative burden on the formal economy, further depressing activity in that sector and creating even stronger incentives for the underground economy. Governments find them- selves trapped in a vicious cycle. The smaller the tax base becomes, the higher the tax rates required to raise a given amount of revenue. But the higher the tax rates, the stronger the incentive for evasion. The extent of tax evasion and its effect on govern- ment revenue is well documented. Norman (1982, p. 23) has estimated that tax evasion in Australia amounts to between 2 and 3% billion dollars at

1984 HIDDEN ECONOMY 219

current rates, imposing a burden of $200 to $350 on the ‘honest’ taxpayer.

Hidden activity also has implications for the expenditure side of the government budget. Low levels of activity in the measured sector stimulate pressure for increased government expenditure and transfer payments. There is also an incentive for those engaged in underground activity not to fully disclose their income in order to maximize their entitlements to transfer payments. This does not necessarily involve outright fraud but perhaps merely the avoidance of monetary exchange. Since the implicit taxation rates on certain transfer payments can approach or even exceed 100 per cent (Gruen, 1982, p. 215). theincentive for underground activity on the part of welfare recipients can be much stronger than non-recipients.

Incivism One of the most serious consequences of the

hidden economy may be the hardest to quantify - namely the erosion of public confidence in the system of taxation and general administration and the ability of the government to operate efficiently and fairly. Recent revelations regarding the extent of tax evasion and avoidance in Australia appear to have undermined public confidence in the system of taxation. This system necessarily relies to a large extent on voluntary compliance for efficient operation. Widespread public acceptance of a taxation system is probably a necessary condition for efficiency and equity. Such public approval and cooperation is much easier to dissipate than to acquire. General Comments

The severity of these consequences depends upon the size and rate of growth of the hidden economy. The extent of tax evasion and its impact on government revenues has been well documented in recent years. This aspect excepted, the review of measurements in the previous section suggests that caution should be exercised in attributing too many of the ills of modem economies to hidden activity. The suggestion that the poor economic per- formance of recent years is primarily a statistical illusion aggravated by misinformed policy is a simple and beguiling hypothesis which warrants consideration. However, the weight of evidence does not support the existence of a hidden sector of sufficient size to make this alone an adequate explanation. On the other hand, the undermining of public confidence in the system of taxation and regulation depends upon the perception of the

hidden economy rather than its actuality. This indeed might be the most significant casualty of the hidden economy.

The hidden economy has some redeeming features. It provides purchasers with goods and services which they may be unable to obtain through formal channels and lubricates the workings of the formal economy (Prager, 1983). This is most clearly seen in highly regulated economies such as the Soviet Union where the ‘second economy’ compensates for many of the deficiencies of the planned economy by reallocating resources (such as raw materials) to where the need for them is greatest. Similarly in Australia, the hidden economy helps to alleviate some of the inefficiencies and inequities imposed by regulations. Unless we maintain that all regulations have the desired consequences and achieve benefits which exceed their costs, we must grant that some hidden activity designed to circumvent regulations has social benefits. Greater benefits might be achieved, however, by removing unwise regulations.

Informal economic activity also confers many benefits on its participants. These include greater freedom, flexibility of working hours and conditions, self-satisfaction and independence. Some, for example Gershuny (1979). Heinze and Olk (1982). and Pym (1980), see the development of the informal economy as the most appropriate solution to high levels of unemployment and the financial difficulties of the welfare State. The positive aspects of the informal economy have been recognized by government policy. In a speech to the International Labor Organization in 1983, the Prime Minister, Mr Hawke, committed his government to support for ‘alternative employment’ to reduce ’the demand for jobs’. This has been interpreted by some people as a commitment to provide financial support for the informal economy.

V Conclusions and Issues The bulk of this paper has concerned

measurement reflecting the focus of most of the economic literature. Techniques of measurement fall naturally into two classes - macro approaches and micro approaches. Internationally, estimates range from 2 to 33 per cent of GDP. The macro approaches tend to give higher estimates than the micro approaches. This suggests that they might be interpreted as upper and lower bounds respectively. While I have deliberately avoided giving yet another estimate of the size of the hidden

220 THE ECONOMIC RECORD SEPT.

economy, my own assessment is that the size of the underground component of the hidden economy lies closer to the bottom end of the range.

If the underground economy is not as extensive as is commonly believed, how do we explain the prevalence of anecdotes about cash transactions, irregular labour services and so on? Even if in aggregate the hidden economy is small, it can be large and significant in many sectors. The government sector is probably exempt from hidden activity and it is likely to be much less prevalent in the corporate sector. Most hidden activity is probably concentrated in the unincorporated sector. The opportunities for hidden activity are not uniformly distributed and some areas such as building and construction lend themselves readily to irregular activity. There is ample scope for a rich supply of anecdotes even if the aggregate size of the hidden economy is small. Moreover, what is small depends upon one‘s perspective. Even if the underground economy amounts to only 3 per cent of GDP, that requires an average expenditure per household in 1980-81 of $841. me hidden economy may be quantitatively small in aggregate yet pervasive.

One of the reasons why a more precise assessment of the size of the hidden economy has not been attempted in this paper is my view that the focus on measurement has tended to attract attention away from other issues which may be more important. Little attention has been paid in the literature to the definitional problem. In terms of the distinction made in Section I, the hidden economy has two components: the informal economy and the underground economy. The division of economic activity between these sectors depends upon conventions which represent a compromise between principle and practice. Both sectors will be stimulated by taxes and regulations. Measurement of the full extent of the hidden economy demands some reexamination of national accounting conventions and definitions.

Another neglected issue involves the causes of the hidden economy. What promotes the diversion of economic activity into the hidden economy? Clearly taxes and regulations are a major cause. What little evidence there is suggests that other factors are also important. Economists could do more in identifying the incentives for indulging in activity in the various sectors.

Frequently it is implicitly assumed that economic activity which goes unmeasured should be discouraged. There are, however, positive aspects to the hidden economy -not the least being that

it provides a (second best) response to regulatory excess. A broader definition of the hidden economy and a better understanding of its causes may promote a clearer perception of the true costs and benefits and lead to policies which encourage the positive aspects and minimize the negative.

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