MODELLING THE PEOPLING OF AUSTRALIA: 1900–1930

MODELLING THE PEOPLING OF AUSTRALIA: 1900-1930 * DAVID POPE

University of New South Wales

I . INTRODUCTION

For three decades after 1860 Australia enjoyed high output and population growth and a generation during which, as Brian Fitzpatrick has written “ ... children grew to middle age without personal experience of depression” [lo, p. 2721. The plunge into severe depression in the early 1890s saw the reversal of established patterns: unemployment afflicted one quarter of the workforce; average incomes turned down; capital inflow all but ceased and net migration not only fell away, but for a time was negative. The three decades following Federation in 190 1 witnessed a prodigious effort by governments to renew immigration and to accelerate the process of peopling Australia. No clearer signal of this intent can be found than the renewed offer towards the close of the first decade of subsidised fares: six in every ten immigrants to set foot upon Australian soil were to be financially assisted. Within these years Australia came to achieve one of the highest population growth rates in the West and immigration from “Home”, as most Australians of the time referred to the United Kingdom, contributed importantly to this result.

The determinants of international migration have been the subject of lively debate since at least Jerome’s ‘push-pull’study of 1926 [15]. It was in fact in thecontext ofthe ‘push-pull’ controversy that Allen Kelley [ 171 first estimated a model of migration from the United Kingdom to Australia, concluding in favour of the ‘pull’ hypothesis as appropriate to explaining flows from the ‘Old World’ to ‘Lands of Recent Settlement’. Two subsequent studies by Pope [ 191 and Richardson [25] modified this finding for Australia, but overall there was a marked consensus: the three were unanimous that wage or income differentials were insignificant, and for two authors, Kelley and Richardson, ‘push’ could be dismissed and the explanation simplified down to a single influence, ‘pull’.

It is not our purpose in this paper to pursue this line of enquiry but to attempt two things which these previous models failed to do.’ First, to explicitly develop and estimate a model of the behavioural relations of the two blades of the Marshallian scissors, rather than mixing supply and demand (under the polyglot terms of ‘push- pull’) in a single equation without regard to the problem of identification. And second, to incorporate in these structural equations key elements of government intervention in the migration process.

*I gratefully acknowledge the helpful comments of my colleagues at the University of New South Wales and two referees. An earlier version of this paper was presented at the 8th Conference of Economists, La Trobe University, Melbourne, in August 1979. ‘For a detailed review of these models see Pope [21].

258

1981 MODELLING THE PEOPLING OF AUSTRALIA: 1900-1930 259

- Gross inflow

11. THE HISTORICAL SETTING

In 1901 when the six colonies federated to become the Commonwealth of Australia their combined population numbered 3.8 million. By 1930 Australia’s population had grown to 6.5 million, net migration being responsible for about 30 per cent of this expansion. The most striking characteristic of these overseas movements was the predominance of one source country. Three quarters of the net arrivals came from the United Kingdom, indeed very largely from the most populated and industrial counties of England .z

Net annual arrivals from this source vaned a good deal over the three decades (CHART I). This almost entirely reflected the size and volatility of gross arrivals; the gross outflow was small and relatively invariant. And, as the reader can see from the chart, about 60 per cent of the gross arrivals were assisted. Our subsequent study for these reasons focusses on annual variation in gross immigration and upon the demand for population additions as expressed through Australia’s assistance programme.

d 60

2 C

0

40

20

0

1901 1905 1910 1914 1920 1925 1930

A wide range of Britons were eligible for assistance. Two thirds of all those assisted by Australian governments were migrants ‘nominated’ by friends and relatives in Australia, a few were nominated by charitable organisations, while the balance were directly ‘selected’ by Australian governments. Among the latter group were immigrants intended for specific work in Australia, namely farm workers, farm lads and young girls for domestic service. Assistance towards the cost of transfer varied

2For discussion of the background of immigrants see Pope [23] and for the demographic and economic effects of immigration during the period, Pope [22].

260 AUSTRALIAN ECONOMIC PAPERS DECEMBER

among these classes and over time but the government contribution cut the mean assisted fare to between one-half to one-third of the third class steamer fare. This certainly would not have been a trivial saving to those pondering the costs of making a new start to their lives. The cheapest contract rate for an adult in 1924, for instance, was f36. Average weekly money earnings in Australia were 94s.4d and 60s. in the United Kingdom. Assuming a marginal propensity to save of . I0 the difference between the assisted rate and no government assistance amounted to about nine months’ savings at UK wages. And as family migration was the norm, our migrant household head needed not one fare but probably enough for two adult passages plus fares for three or more children. In the years to 1914 assisted immigration was in the hands of the states. Following the war the Commonwealth largely assumed the costs and solely determined the subsidies, with the Imperial government paying half the bill following the Empire Settlement Act of 1922.3

Nationals from other countries were not so favoured as those from the United Kingdom. With a few minor exceptions they were not eligible for any assistance, and from many countries immigrants were actively discouraged. One of the first acts of the newly created Commonwealth government was to give power to immigration officers to refuse entry to those who could not pass a dictation test in a language nominated by the officer. This sought in no uncertain terms to prohibit Asian immigration. Later, in the 1920s, when the effects of the United States Immigration Restriction Acts were felt in a larger inflow of southern Europeans in Australia, the Commonwealth government imposed a system of quotas on visas issued from some embassies in Europe and steeply increased the landing money requirements of southern Europeans to between E50 and f200. This compared with the f 3 required of United Kingdom immigrants, these even being eligible for a loan to cover this requirement. Thus it was not only a matter of keeping Australia ‘white’. As the Australian Prime Minister, Bruce, in a letter in 1924 to the British Secretary of State recorded, it was his government’s policy to maintain Australia ‘98 per cent British” 13. If Australia were to populate, develop and defend her ‘vast open spaces’ then she needed immigrants and the principal source of these was clearly seen to be the United Kingdom.

The idea of encouraging a redistribution of population between the United Kingdom and Australia was certainly not new, but it gained the special support and backing of the British government in the 1920s.4 By the Empire Settlement Act of 1922 Britain agreed not only to share the cost of passage assistance with the Commonwealth government of Australia, but also undertook to share interest payments on certain government loan borrowings on the London market, the purpose of which would be to promote land settlement and development in Australia. The war had strengthened the sentiment for a strong and united Empire and for policy makers in Whitehall, the economic climate in Britain in 1920-21 (her mounting unemployment and the

’For three years immediately after the war the British government also granted free passages to ex-service personnel and their families who had been approved as nominated or selected immigrants by the Australian states.

4The only British machinery for the encouragement of emigration prior to the end of the war was the Emigrants’ Information Office established in the late 1880s to diffuse information about the dominions.


declining prospects of her staple exports), also did much to feed their enthusiasm for a redistribution of resources.

Capital expenditure on land settlement and development works undertaken under the terms of the 1922 Act was, however minor compared with Australian state governments’ loan raisings in London for public works in general. Colonial governments in Australia, and then after Federation in 1901, state governments, played the major role in providing infrastructure for the economy, railways, roads, irrigation, power, communications and so forth. Close to half of Australia’s capital formation in the period was undertaken by governments. The determinants of public investment were complex, but one element in much of it was the desire to develop Australia, to expand job opportunities for residents and new arrivals, and directly and indirectly, to support the living standards of a larger, albeit handpicked population. There was also a hint of these goals in other policies too, in for instance the adoption of high tariff protection in the 1920s, in price support schemes and subsidies, and in the marked preference shown to local producers when government contracts were awarded.

111. THE MODEL

a. Some Preliminary Concepts

The main features of the model, and coincidentally where it departs importantly from earlier studies, are in the distinction drawn between contemporaneous labour and population markets, the characterisation of migration functions in these markets as ‘excess’ demand and ‘excess’ supply curves, and the explicit modelling of public policy.

To begin with, migrants contribute to both the workforce and population of a region. Contemporaries were well aware of the distinction between additions to the current workforce and additions to the population at large. Gullet, the Superintendent of Australia’s immigration office in the early 1920s, recorded that, ‘A married man and his wife with say four young children, is a preferable immigrant to three or four single men’ [2]. The former partly increased the current workforce, but also meant an ever growing army of producers, consumers, taxpayers and defenders into the future. The literature on the determinants of migration, as distinct from its consequences, has almost exclusively concentrated on current labour market aspects of migration, ignoring the broader implications of the population market. Of course on the supply side, the distinction is not critical, for there is a nexus between the population and labour markets, labour supply being a proportion of population supply. On the demand side, however, there is no such nexus, for demand for labour is an offer to hire workers now and total demand for labour an aggregation of wage bids by individual employers. By contrast the demand for population by Australia was very largely the outcome of collective decision making via the agency or government, and it hardly ever entailed a specific wage bid; the demand for people was not simply the contemporaneous demand for workers.

As labour and population transfers from the United Kingdom were seen as close substitutes for Australian born workers and residents, it is useful, analytically, to at


least begin by regarding migration as a process that made the Australian and UK markets subsets of the total (Australia plus UK) market. A fair characterisation is that there was no separate demand for migrants per se, nor supply of migrants per se. Rather the migrant supply and demand curves represented 'excess demand' and 'excess supply' curves, excess demand being Australian demand minus Australian supply and excess supply being UK supply minus UK demand.

Yet insofar as there were lags in markets adjusting, annual migration would only have moved towards long run equilibrium. Indeed if lags were substantial, the annual migratory flow would have depended more on the determinants of the speed of adjustment, than on factors behind the long run 'excess' supply and demand curves. Assuredly an equilibrium distribution of population could not be achieved quickly; for most of the period Australian policy makers spoke of achieving a more optimal distribution over the course of 20 years or more. And even within the context of short term demand and supply, of course, disequilibrium may have prevailed insofar as the intentions of demanders and suppliers were not realised, a point to which we return shortly. We turn first to the structural equations of the model.

b. The Behavioural Equations 1. Population transfers: migrant supply Lack of information about overseas job markets together with liquidity constraints

on meeting relocation costs meant a slow adjustment process towards long run migrant supply (i.e. towards the UK excess supply curve). Our central hypothesis is that this speed increased when the net rewards of migrating rose and when liquidity constraints on meeting relocation outlays were less severe in the following way

M ; = a: + a fnt RYD, + afn t Ft + asnt TCt + a f n , RSCt + a:MAL + E; (1) where:

MS = R Y D

F = TC =

RSC

n = MAL

s = t =

ao...a5 = s s

Es =

supply function of gross UK arrivals in Australia the real income differential psychic costs of moving real transport costs per migrant real search costs a measure of the attractiveness of destinations other than Australia UK household heads aged 20-45 years supply time measured in years parameters to be estimated error term

The first four variables in equation 1 encompass the net rewards to Britons of emigrating to Australia, namely the wage gain less the costs of transfer. The usual simple hypothesis of wage gain is modified in a number of ways as set forth in the expansion of R Y D below,


where:

0 = average years to retirement of UK household heads (1 - U) probability of being employed, U being the unemployment rate

NW = nominal wage rate CPI = consumer price index

H average hours per normal working week w = weights A = Australia

UK United Kingdom t = time measured in years Other variables as previously defined.

Thus wages in both Australia and the UK are adjusted for hours worked in the normal working week and by the probability of obtaining employment at those rates. In addition, as the absolute gain from the differential in probable hourly earnings depended on the years to retirement of decision makers, earnings have been weighted by the average years remaining in the working lives of UK household heads.

Household headship has also been integrated into the model as a means of aggregating individual behaviour. The larger the number of household heads ‘at risk’ to emigration, then the greater the aggregate response to a given incentive, and for this reason the real income gain, R YD is weighted by n, the number of household heads, as are the three costs of emigrating to which we now turn.5

Of these, the first in equation 1 are the psychic costs of leaving home and friends. These costs, it is hypothesised, varied negatively with the stock of friends and relatives who had already emigrated to Australia, that is,

where: y = survival probability among past arrivals Q = net migration J, most distant year in which previous net migration alleviated F

Other variables as previously defined.

The second cost, that of transport, TC, is posited as, t

5This is analogous to expressing the dependent variable, migration, as a proportion ofthe ‘population at risk’, that is M / n , except that in this form the constant term is divided by n and the error structure, if homoscedastic in the levels (M) equation, will become heteroscedastic in the proportions equation. Conversely, if the variance of the errors in the levels equation increases as n increases, then using M / n as the dependent variable would remove such heteroscedasticity. It transpires that empirical testing revealed no correlation between the (squared) residuals in the levels equation and n, which is to say that heteroscedasticity, at least in the dimension n, is not present.

264

where:

AUSTRALIAN ECONOMIC PAPERS DECEMBER

CI = adults c = children

PC = shipping companies third class contract rate S P A = passage subsidies per migrant issued by Australia

S P u K = passage subsidies per migrant paid by UK government with

The numerator of equation 4 yields a weighted average fare in nominal terms and to allow for the constraining effects of the household budget on emigration, this cost is deflated by the liquidity base of the household, represented by householders' probable recent savings-income levels.6

The last cost considered in this paper,' the real costs ofjob search, RSC, needs to be similarly adjusted by the liquidity base, even though in this instance the numerator is an index of money values, not money itself. For although no dollar values can be assigned to search costs, the duration of search would have varied with Australian unemployment rates, whilst variation in costs during search would, we suggest, be reflected in Australian consumer prices. Rigidities in the labour market and in information flows makes it likely that the relation between search time and Australian unemployment may not, however, have been a simple linear one, hence the non-linear specification of this relation in equation 6 below,*

where all variables are as previously defined. So far the analysis has been conducted as if the decision maker faced the choice of

staying home or of emigrating to Australia. He or she may, in fact, have compared the net gains expected in Australia with those expected in other destinations, as well as his/ her expected income in the United Kingdom. Degrees of freedom preclude testing the hypothesis in this form: it would involve adding a wage gain variable and three unlike cost variables for each alternative destination. The last variable in equation 1,

Given the nexus between savings and income, savings (taken as the liquidity base) may be gauged by UK wages adjusted by the likelihood of employment at those rates. T o attempt is made here to estimate foregone earnings associated with passage time. For discussion see Pope ~ 2 0 , pp. 406-4081.

RFirst, because of rigidities in the labour market when unemployment was low, further reductions may not have indicated the increased number of job vacancies to the same extent as did falls in UA when unemployment levels were higher. Second, in times of extremely high unemployment, local knowledge would have been vital in discovering the few available job openings and as new settlers, migrants' lesser knowledge of local conditions disadvantaged them more than at other times. The squared deviation term in equation 6 performs the function of stretching the unemployment function at both extremities, but in so doing eliminates the information on whether CIA is above or below the mean level, 0. The modulus deviation term restores this information; if .+> 0, the modulus deviation term takes on a value of

+ I , whereas if .;" < 0, its value is -1.


MAL, is the outflow from the UK to destinations other than Australia which is taken as an index of the attractiveness of the set of alternative destinations.9

2. Population transfers: inverse demand

Whilst migrant demand reflected both Australia's demand for population and her total population supply, the predominant influence in the early twentieth century came from the side of Australia's demand for population."J Australian governments did many things which directly and indirectly affected the inflow of UK migrants. They directly influenced the cost of transport, and by actions which supported living standards and employment in Australia, also influenced wage gains and search costs of migrants. And governments were the vehicle by and through which Australia's demand for population was expressed. Australian governments provided the corporate machinery (the stage and corridors of parliament) by which community, group and individual claims (including those of politicians) could be resolved. By legislative enactments and ministerial actions, governments also provided much of the machinery to implement such resolutions. Of course, the formulation of public policy was complex. Group claims were diverse; some were more co-operating than competing in nature, and some were constantly voiced rather than variable forces behind policy. The weights assigned to arguments in debate and the resolution of differing claims also varied in accord with the political complexion of governments and varied too with the strength with which claims were pressed, which partly reflected the changing net gains of groups resulting from past resolutions and decisions." Although we cannot quantify and sum the 'public valuation' of migrants, it is possible to distil some of the decision making process indirectly from the variables behind the valuation and in turn to derive a demand relation.

A detailed account of the historical forces bearing upon Australia's desire for migrants is given in Pope [20]. Briefly, among the factors which it is posited affected demand were Australia's perceived defence needs, DEF, demand associated with public capital projects, ZG, union and employer pressure on government for more/less immigrants, EMC, farm sector demand for workers and farm lads, A Q, and concern after World War I with market prospects for Australia's traded output, T.

Australia's changing view of her defence needs is represented in equation 7 by defence expenditures over recent years, net of direct war outlays and repatriation costs, and expressed as a proportion of national income, that is,

DEFt d ( Z / N G N P ) j (7) j = t - - 4

9MAL is not milltiplied by n as it does not relate to potential (at risk) movers but actual movers. 10The two factors determining Australia's total supply (netted of UK arrivals) are net inflows from non

UK ports and Australia's natural increase. Net inflows from non UK ports were small (in the case of southern europeans the positive net inflow was the cause of alarm not joy) and although Australia's declining birth rate stirred the emotions of a vocal fringe at the beginning of this century, the secular trend was generally accepted, see Neville Hicks [14].

"A good example of this is the willingness of trade unions to support immigration in 191 1-12, but their increasingly fierce opposition as unemployment, which they related to the UK migrant intake, subsequently rose.

266

where:

AUSTRALIAN ECONOMIC PAPERS DECEMBER

Z defence outlays netted of war and repatriation charges

Rises in both DEF and government capital works, I G , are seen as having positively influenced demand. The higher the fears for Australia's security, the greater the demand for immigrants as defence assets,l2 and as government capital projects constituted assured jobs for a growing workforce while the resultant infrastructure met the needs of a growing population, then the more public works in progress, the happier governments of the day and the public at large were to increase immigration. In the case of EMC, pressure from employers to increase immigration tended to fall and that of employee groups strengthen as the labour market slackened. However, the reaction of government to these pressures was not smooth. For instance, in terms of encouragement offered to UK immigrants, the doors were flung wide open following public enquiries into the shortage of labour in 1911-12, but slammed tight in 1930 when governments faced the opposite circumstances. It is postulated, therefore, that the impact of unemployment was disproportionately large when labour shortages or surpluses were acute.13 Allowing also for the possibility of a time lapse in the reaction of unionists and employers yields,


t r . L

where: EMC = index of employer/union pressure for more/less migrants

With regard to the farm sector, it is hypothesised that pressure on governments to recruit farm workers and young lads for training in rural work varied positively with harvest forecasts and the state of rural expectations generally,I4 these being represented by,

t

'*To the extent that expenditure on defence and on attracting more people from Britain were seen as substitutes rather than complements(as conjectured here), DEF's coefficient is likely to be an underestimate of the impact of defence fears on Australia's demand. For further discussion see Pope [20,

"TO reflect this response to extreme situations, the unemployment series is stretched at both ends which is effected by the signed quadratic form shown in equation 8. 14AQ in equation 9 is a combination of agricultural output during the current and preceding year. The

annual demand for land 'settlers' could also be modelled, however, very few migrants were settled directly and immediately on the land. Despite the rhetoric of the era, land was finite, expensive t o acquire by repurchase or to cull from the natural bush. And given the prices a t which state government Land Boards disposed of it, long queues of resident Australians formed. In practice the approach adopted by most states was one of 'infiltration'; immigrants could begin as farm labourers, time and frugality would equip them with experience and a small amount of capital, the requisites for successful settlement.

pp. 251-254, 418-4191,


where:

A Q = demand for farm workers and farm lads A P = real agricultural production

Australian policy makers also voiced concern after World War I with the prospects for Australia’s traded goods, especially with some rural exports: if Australia was to be kept white, British, prosperous and safe, she needed UK migrants, but she also needed expanding markets for traded goods produced at the hands of the greater numbers. In the rhetoric of the 1920s this was capsulised in the call for ‘men, money and markets’. The binary variable T ( T = 0 prior to 1920,l thereafter) is included in the demand relation in an attempt to assess this negative influence.

In addition to these factors, changes in Australia’s demand for UK population depended on the ability of governments to finance immigration and the immediate price involved. The budget or wealth constraint in our model, BC, employs nominal and real income as a measure of the government tax and loan bases from which the programme was financed. 15

t BC, = C ( w j R G N P j + wjNGNPj )

j = t - I

where: BC = budget constraint

R G N P real gross national product

As for the average cost or price per arrival, we take the most direct price paid, S P A , passage assistance per migrant. Governments also met some of the capital requirements of migrants, hence these public capital outlays might be construed as costs too. However, a number of considerations lead us to expect opposing signs of influence for investment and passage outlays. What is critical for our purposes here is how such outlays were perceived by those living 60-70 years ago and not how similar outlays might be viewed today, and in this regard public investment was mostly seen then as a justification for wanting more people, not as a cost of having migrants.

Moreover, investment programmes were broader in purpose than the direct outlays on assisted passages, and this obscured the marginal costs attributed to migrantsperse in such programmes. Thus while public investment should be included as a determinant of changes in demand it should be included as a positive not negative influence. On the other hand, it is clear that in revising passage assistance rates, policy advisers consciously and directly assessed these as costs. Farrands, Secretary to the Development and Migration Commission, in a lengthy document for the Prime Minister summarised,

15Tax receipts were influenced by changes in income (chiefly real income in the case of per item indirect taxes, chiefly nominal income in the case of ad valorem indirect taxes and the graduated income tax) and a case might also be made for thinking that the ease of borrowing at home and abroad was influenced by income performance - rising income increased the supply of domestic savings and output performance influenced the attractiveness of Australia in the eyes of UK investors.


The question of further reducing the assisted passage rates is of course one of government policy, and must be considered from the following viewpoints: (a) whether further reductions in passage rates are likely to lead to considerably increased migration; and (b) whether the Government is justified in increasing, and is in a position to increase, its annual expenditure on assisted passages. It is fairly obvious, I suggest, that further reduced rates will result in an increased flow ... [3].

Farrands then went on to offer estimates of the extra numbers and the cost so incurred. Nor was the projection of extra numbers relative to costs, a procedure of analysis adopted only after the establishment of the Commission [4]. Further, subsidy levels and numbers to whom these were offered could and were varied within years. For instance, when total arivals looked to be adequate or excessive in light of rising unemployment, then the processing of applications for assistance slowed down and the criteria for granting subsidies were more rigorously enforced, which in turn influenced total arrivals. In this way non-price rationing was used by governments to alter, in effect, the denominator of the average subsidy: both price and non-price rationing effected changes in S P A .

The demand relation is summarised in equation 11. As we are particularly interested in the determinants and ramifications of government assistance programs, the relation has been written in its inverse form with SPA as the dependent variable on the LHS, thus: S#id=add+a!dDEFt+a2 id It G +a3 id EMCt+a4 id AQt+as id BCt+a6 id Tt+a7 id M t + t t id

where: (1 1)

SPAid = inverse demand function for gross UK arrivals in Australia ad d...a!d = parameters to be estimated

Other variables as previously defined. tid = error term

3. Labour Transfers

While it is with UK Population transfers and not simply labour flows that this paper is concerned, one question that must be addressed before estimating the model is the relation between these two.

By definition those migrants offering for work in Australia were some proportion, A , of the total supply of UK arrivals,

ML; htMf

where:

ML: supply function for gross UK labour arrivals in Australia A = workforce participation rate amongst UK immigrants

Other variables as previously defined. Demand for UK migrant labour is posited as the total demand for labour in

Australia minus the supply of Australian labour. Equation 13 specifies the demand for


labour in Australia as dependent upon government capital works and the private sector's demand for labour, the latter's determinants being input and output prices and the expected short run level of output, a variant of Jorgenson's familiar specification [151.

where:

MLf = demand function for gross UK labour arrivals in Australia D G N P = gross national product deflator

parameter measuring employer's sensitivity to input / output prices W total Australian workforce exclusive of current UK immigrants

PO ... P2 = parameters $fL = error term


c.

Equations I , 11, 12 and 13 are, of course, ex ante concepts and it remains to ask whether there is reason to believe that the plans of demanders and suppliers were met.

On the supply side, since emigration was not compulsory, the expost migration series cannot exceed ex ante supply (equation 1). But it may have fallen short in 19 11 and 1912 as there is some evidence of shipping shortages at this time, a consequence of which is that the model might be expected to overpredict numbers of immigrants in these years. In the case of demand (equation 1 l), governments did have crude targets based on numbers to be subsidised and predicted free arrivals; attempts were made, or at least contemplated at times, to directly affect the unassisted inflow,l6 though it was overwhelmingly the assisted dimension by which governments sought to vary the total movement. Targets were fluid things, conceived against past performance and current circumstances and constraints. Although politicians freely nominated lofty fixed targets (Hughes in the early 1920s spoke of 100,000 per annum), they were more fluid than this suggests. Indeed, Hughes' government provided in the Budget Estimates for 1922 only sufficient funds to cover the passage of '... approximately 30,000' adding that '... the government regrets very much that the prospects for the year (the postwar slump) ... are not to warrant a very much larger expenditure on passage money"9, pp. 1813, 18161. And plans could also be varied, as we have said, within thefinancialyear.1'

Ex Ante - Ex Post Translations

"For instance, Gullet cabled Australia's London Office in May 1921, 'Unemployment acute New South Wales considerable distress. Same time considerable numbers unassisted third class passengers arriving. Suggest you take any steps temporarily discourage these bookings' [6 ] .

"For this reason the difference between Budget Estimates and realised expenditures do not accurately reflect discrepancies between ex ante - ex post demand.


Generally, it is our impression that these practical short term plans, as distinct from optimistic assertions and political rhetoric, were by and large realised.18

In the case of migrant labour demand (equation 13), the evidence is abundantly clear. As employers could not be forced to hire workers in excess of their requirements (and except at the peak of the pre-war boom the period was not characterized by general labour shortages), then ex post numbers hired corresponded to numbers demanded ex ante. But on the supply side (equation 12), ex ante plans were not reflected in the number of workers hired, as residents along with UK job entrants encountered a degree of involuntary unemployment. Nor, related to this, were wages freely determined, for increasingly they were set by government wages boards, tribunals and courts. These bodies looked largely at unemployment rates and inflation, with a switch in emphasis from the former to the latter after World War I.I9 That the labour market did not clear (unemployment ran at about 8-9 per cent during the 1920s), probably reflects the presence of rigidities, and in part, the insufficient weighting of unemployment by the authorities. Leaving these points aside, what is clear is that to complete the model a wage fixing equation is required, equation 14,

N W p = 40 + 41 U A + 42 UAD + 4, CPIA + 44 CPIAD + E (14) where:

D = 0 prior to 1922, 1 thereafter 4n ... $4 = parameters


Formally, then, our ex anre - expost translations may be written,

Ms = M , (15)

MLS = M L , (17) SpAid = S P A , (16)

M L ~ = M L S - u * [ x , M + w ] . (18) and,

After appropriate substitutions (equations 2 - 6 and 15 into 1; 7 - 10 and 16 into 11; 15 and 17 into 12; 14 and 18 into 13), the 18 equations and 18 LHSvariables collapse

1RIt is important too, to distinguish between rhetoric and demand as an economic concept - politicians could be disappointed by numbers arriving though this does not necessarily mean that Australian demand was unsatisfied, insofar as the price may have been known to be toolow to obtain the numbers. Following the Migration Agreement of 1925 by which Australia was to bring out 450,000migrants over 10 years, the Commonwealth Budget tediously reported targets of 45,000 assisted migrants. Yet the money allocated for passage assistance was only enough, in 1925-26 for instance, to cover 31,000 migrants according to the Migration Office’s own submission to Treasury. Similarly, while Australia’s London Office reported in 1928 that, it has ‘... been unable for some time to meet the full requisitions for Boys and Household Workers’, it pointed out that these groups were highly sought after in England and that Canadian competition for young boys was acute; Canada offered free travel and an interest free loan of f500 when boys attained 21 years of age. The Director of Australia’s London Office, Colonel Manning, wanted the subsidies increased ‘to obtain the numbers’ [7]. But while this was considered, his advice was not taken.

I9From 1922 the ‘basic wage’ was indexed to consumer prices, though there were some claims for ‘secondary wages’ for skills which were largely assessed in terms of the relative degree of excess demand for labour.

1981 MODELLING THE PEOPLING OF AUSTRALIA: 1900-1930 27 I

into the four migrant functions, Ms, SPAid, MLSand M L d These jointly determine the four endogenous variables that remain after the substitutions, M , N W A , UA, S P A . The two equations to be estimated are 1 and 11 following the above substitutions, which having been done, may be termed, 1’ and 11’.

For these two equations to be identified both must exclude at least three variables that can assist identification. On Franklin Fisher’s classic Jacobian test [ 1 I], each linearly separable non-linear function of exogenous and/ or endogenous variables in equation 1’ and 11 ’ so assists. This means that equation 1’ has more than 17 such excluded variables ( T and the linearly separable components of the LHS variables in equations 7 - 10, 12 - 14), while equation 11’ has more than 16 such excluded variables (the linearly separable components of the L H S variables in equations 2 - 6, 12 - 14). Our structural equations are thus amply identified.

IV. EMPIRICAL RESULTS

The principal procedure in estimating the two equations of interest is OLS, but these results are supplemented with a two stage regression analysis (ZSLS), and it is here that the other equations of the collapsed model are necessary for the reduced form estimates. A scanning technique was also used to generate maximum likelihood estimates of p, which were used in correcting for first order serial correlation. Additionally, small sample Monte Carlo studies suggest that corrections based on I; reduce the mean square error of the regression estimates. The superscript B to an equation denotes such a correction. To reduce rounding error all variables were standardized to zero mean and unit variance.

a. OLS Estimation

Precious degrees of freedom impose a constraint on the number of variables included in any one equation. Taking supply first, equations and 2 in Table I tentatively confirm the positive effects upon migration of real income gains, and of the presence of friends and relatives already resident in Australia. Both equations confirm the negative effect of transport costs on migrant supply but job search costs, while exhibiting the expected negative sign fails the ‘t test’ and MAL possesses the wrong sign. Given lags arising from delays in the receipt of information concerning Australian circumstances, and lags too in responding - from habit persistence and the time involved in transferring residence - we respecified the model with lagged values of the pecuniary costs, and in equation 3 both were found significant. Though not reported, using the same income hypothesis as that of equation 2, did not alter this conclusion nor the level of significance of the estimates.

Equations 4 - 7 explore the perverse sign of M A L and also alternative specifications of expected income gains and relocation costs. Examination of the residuals revealed that the overwhelming errors were underpredictions in 1910-12, the very years it will be recalled of shipping shortages. As 1910-12 were also years of record employment in Australia it is possible that the residuals arise from mis-specifying the full impact of U A on search costs, hence on immigration, and if this were so, then

TA

BL

E I

Mig

rant

Sup

plyt

t (O

LS)

h) .I N

i%f

ntR

YD

t n

rRY

Dt

u(n

tRY

Dt)

u(n

tRY

Dt)

nr

Ft

nrT

Ct

ntT

Ct -

nrR

SCt

ntR

SCt - 1

MtL

R2

w

DW

p

Equ

atio

n --

Wa

'"b

W

a

Wb

iA iB iA

iB

jA

jB

iA

-B

4

- .oo

(

.OO)

- .0

2 (-

.09

)

.oo

.44

( .O

O)

(3.1

7)**

*

- .0

6 .2

9 (-

.19

) (I

.46)

*

.31

.53

( 1.

90)*

(4.

38)*

**

.24

.42

( 1.

09)

(2.4

7)**

*

.06

.05

( .5

5)

( .2

0)

- .0

1 .3

7 (-

.06

) (1

.81)

**

.56

- .49

.0

1 (4

.50)

***

(-3.

15)*

**

(- .0

7)

.42

- .3

7 - .

07

(1.6

7)*

(-1.8

1)**

(-

.57

)

- .52

-

.04

(-2.8

8)**

* (-

.20

)

- .34

-

.06

(-I. 6

2)'

(- .4

2)

- .4

5 (-2

.87)

***

- .3

1 (-1

.56)

.

- .65

(-

3.90

)***

- .3

4 (-1

.63)

.

.36

t (2

.61)

.I7

t (1

.27)

.33

t (2

.10)

.I6

t (1

.18)

-1.3

3 .4

1 t

(-1.9

4)**

(3

.51)

-1.6

3 .2

6 t

(-2.2

9)**

(2

.40)

- .0

5 .4

3 t

(- .

20)

(3.2

9)

- .34

.3

2 t

(-1.

82)*

* (2

.92)

.75

.69

1.30

.39

.24

1.44

.6

0

.66

.59

.97

.37

.25

1.34

.60

.83

.80

.98

.70

.64

1.40

.6

0

.79

.68

.81

.62

.56

1.50

.7

0

TA

BL

E 1

(con

tinue

d)

&; n

,RY

D,

ntR

YD

I u

(n,R

YD

,) u

(nfR

YD

t)

ntF

t nr

TC

, n

rTcI

- I

n,R

SC,

ntR

ScI

- 1

MfL

R2

D

W

p E

quat

ion --

'"b

wa

"'b

.38

(2.2

2)**

.44

(2.65)***

26

(1.30)

.62

(3.92)***

.43

(1.56).

- .I

4 (-

.53)

- .15

(-

.65)

- .45

(-2.78).

- .2

8 (-1

.40)

.

- .63

- .30

(-3.29)*** (-1.28)

- .28

- .07

(-1.

11)

(- .33)

- .73

(-2.45)***

- .37

(-1.5

2)**

- .22

.50 t

.78

.72

1.00

(-

.93)

(2.6

8)

- .35

.30 t

.57

.45

1.50

.8

0 (-1.83)**

(2.0

0)

- .80

.48

t .78

.74

.86

(- .38)

(2.65)

- .39

.36 t

.60

.52

1.72

.80

(-2.0

7)**

(2.65)

- .42

.71

.66

.72

(-2.30)'.

- .44

.45

.36

1.48

.70

(-2.46)**

Not

es 1

0 T

able

I

tt t

0

8

8.

8.8

wa

Wb

w1=

w-,

.5

wa,

wc

regr

essi

ons

excl

ude 1914-19

coef

fici

ent h

as w

rong

sig

n t

stat

istic

s ar

e in

par

enth

eses

below e

stim

ated

reg

ress

ion

coef

fici

ents

si

gnif

ican

t at t

en p

er c

ent

leve

l (on

e ta

il te

st)

sign

ific

ant a

t fiv

e pe

r ce

nt le

vel (

one

tail

test

) si

gnif

ican

t at

one

per

cent

lev

el (

one

tail

test

) di

stri

bute

d la

g w

eigh

ts o

f

dist

ribu

ted

lag

wei

ghts

of

in e

quat

ions

(4) an

d (6) i

n te

xt

in e

quat

ion

(4)

in t

ext

are

the

prop

orti

ons

of a

dults

and

chi

ldre

n in

f

wo

= .2

5,0-

1 .5

0, W-

2 .2

5

WO

=O,W

-I =.

67,~

-2=.

33


MAL, which also peaked in these years, might be capturing this omitted job search effect. Some alternative functional forms of search costs were tried, including entering unemployment in its inverse squared form, R3C. After correcting for serial correlation, lagged search costs in this form were significant, although neither the sign of M A L was altered, nor were the under-predictions greatly reduced.

One possible explanation for the sign of MALis that it reflects bias which may have entered via the simultaneous effects of Australian emigration on the UK outflow and vice versa. In this case a more direct measure of wage gains in alternative destinations might be superior to M A L in that such a measure could be presumed to be freer of simultaneity bias. But to this we must add that any measure of wage gains to be had in other countries which abstracts from the various associated costs, omits important variables (that this is so can be deduced from our Table I), which introduces bias. And any direct measure incorporating the net rewards of emigrating to several alternative destinations would embody some fearsome problems of aggregation. Nonetheless future research should canvas this avenue.

Equation 4B and the remaining ones provide additional information of the significance of the other determinants. It was initially postulated that UK migrants took into account the risk of unemployment in assessing their earnings streams. Accordingly, hourly wage rates were adjusted by the probability of employment in each country. Yet, migrants may have viewed future jobs as tenured positions, this alternative specification is distinguished by the prefix u in Table I. Two lag structures have also been investigated, a set of declining weights for the past year and the year immediately preceding it, denoted as w, and an inverted 'V' system of weights denoted as wb.20 Within the bounds set by degrees of freedom it was not possible to distinguish between these alternative specifications. Thus in equation4 (and in equations 2 and T ) , whilst differences in real income adjusted by the likelihood of employment were significant, substituting unadjusted values of R YD into those equations yielded similar results. Nor, over the range of equations estimated has it been possible to clearly distinguish between the two lag structures. However, unlagged differences in real incomes were also tested and performed poorly.

*OAn inverted ' V', because migrants had only limited information about the current year (the year in which they depart), hence were unlikely to give it as much weight as the immediately preceding year. Years further back may have received less weight. One structure which is not explored is the simple geometrically declining weights model which employs migration lagged one year, M(r - I), as a n explanator. Though it is plausible that migrants attached progressively descending weight to observations further back in time, M(r - 1) is subject to a range of interpretations, which obscure its meaning. In addition to the above interpretation it has also been seen as capturing the impact of friends and relatives who had previously migrated (Phillip Nelson [7], Belton Fleisher [12], Allen C. Kelley [I 71 and Michael Greenwood [13]). More recently it has been taken as a stock adjustment model towards equilibrium in labour markets (Jeffrey Williamson [26]). Finally, even if the first interpretation is put on M(r - I ) , including this term creates other problems where a number of determinants of migration are included. It becomes necessary to assume that the identical set of geometrically declining weights apply to every RHS variable, otherwise the Koyck transform is impractical because it absorbs too many degrees of freedom, compared to entering explanators as pre-weighted sums of past values as in our model.

275 1981 MODELLING THE PEOPLING OF AUSTRALIA: 1900-1930

Finally, the presence of friends and relatives in Australia appears to have had a significant effect upon migration, which is not too surprising given the ‘nominated‘ system. Yet this raises doubt as to what the variable actually measures, reduction in psychic costs of moving and/or the fall in pecuniary costs via friends and relatives alleviating these. Another problem is with the time dimension of F. In equation 1 the stock is of those who had migrated over the preceding 15 years, but when 1(1 was defined over 10 years the variable proved insignificant. It may have been that the stock was influenced by such things as the 1890s depression, the pre-war economic boom and the war years, and that the 10 year stock captures these events differently. But that the significance of the stock is quite so sensitive to plausible variations in its time span suggests the need for caution. An alternative means of assessing the influence of friends and relatives is the inclusion of migration lagged one period, but this variable is subject to even more obscurity in interpretation than the above stocks.*’

In general then, over the range of equations estimated, lagged real income differences proved to be a consistently significant explanator of migration, although the two sub-hypotheses could not themselves be distinguished. Table I also strongly confirms the two pecuniary costs as significant. That, after adjusting for serial correlation, lagged search costs were consistently significant while unlagged search costs were not, is relatively clear evidence of a lag. Evidence is less decisive on the lag structure of the second cost: when entered separately both lagged and unlagged transport costs were generally significant. The ‘free form’ estimates of equation 6, however, provide some support for the hypothesis that lagged values were the more relevant in the decision to migrate.

Turning to Australia’s demand for UK population, four variables were found to be significant, though again not all of these could be estimated together. The budget- wealth constraint was highly collinear with public investment and for this reason the two have not been included in the same equations. Run separately both possessed the predicted positive sign and both were highly significant, albeit omitting the correlated variable means that the coefficient of the included variable may warrant less stars than actually received in Table 11. Equations 8 - Tf also suggest that labourand employer group pressure, EMC, was significant in shaping changes in Australian demand for migrants.

The fourth significant factor was the binary variable, T, indicating the presence of a negative force after the war on demand. This factor, we have argued, was the greater concern of policy makers after the war with market prospects for traded goods produced at the hands of an increasing population. Interestingly, economists in the 1920s saw the Australian tariff, specifically its upwards jump in 1920/21, as shifting the demand for migrants outwards after the war. This is not inconsistent with the sign of the binary variable. It suggests, rather, that concern for export markets was perhaps even stronger than our results show.

The remaining variables AQ, M and DEF all appeared insignificant determinants of SPAid. That farm sector demand was so, could reflect the fairly light weighting

*‘See footnote 20.


TABLE I1 Inverse Demand?? (OLS)

Equation &if I F EMC, AQ, BC, T M , R2 D W p

8 A

riB

iA

iw

-A 10

-B 10

-A 1 1

-W 1 1

.OO 1.06 - .30 ( .OO) (6.2S)*** (-2.62)**

-.08 1.04 - .21 (-.27) (4.13)*** (-2.13)**

- .30 .76 .73 .88 (-1.71)*

- .s4 .63 .S7 1.90 .70 (-2.67)***

-.oo - .38 1.87 -1.17 .88 .86 1.40 (- .OO) (-4.74)*** ( I 0.0 I)*** (-6.20)***

.02 - .32 1.97 -1.27 .SO .77 1.95 .40 (-.23) (-4.00)*** ( 7.83)*** ( 5.63)***

.oo 1.0s - .30 .03 - .32 .76 .71 .89 (-.17) (S.98)*** (-2.55)"' ( .17) (- 1.4S)*

.02 1.0s - .22 -. 19 -3.75 .64 .S7 1.67 .60 (.OS) (4.31)*** (-2.28)*** (-.83) (- 1.3S)*

.oo 1.04 - .29 ( .OO) (3.60)*** (-2.28)**

-.05 1.09 - .23 (-.23) (3.97)*** (-2.1 I)**

- .29 -.02 .76 .71 .89 (-1.33). (-.lo)

- .49 -.02 .63 .S6 1.80 .60 (-2.44)*** (-.12)

Notes ro Table II regressions exclude 1914-19 r statistics are in parentheses below estimated regression coefficients significant at 10 per cent level (one-tail test) significant at S per cent level (one-tail test) significant at 1 per cent level (one-tail test) in expansion of EMC in equation (8) in text in expansion of BC in equation (10) in text in A Q in equation (9) in text

given to the short term demand for rural labour in Australia's aggregate annual demand for migrants. A related factor is that among the arrivals were boys brought out for training as farmers at state and charitable schools and demand for these may not have been tightly tied to harvest prospects and the very short term requirements of the farm sector.

With regard to M, while the result might be due to measurement difficulties,22 economic theory offers two reasons for a negative though insignificant relation in the

22From the first order conditions of cost minimisation marginal cost should be mapped against the quantity of M . As governments had some monopsony power, price would only approximate marginal cost - the latter would be somewhat higher (given a positively sloped supply curve), though positively correlated with it. We have used price as a proxy for marginal cost.


‘price-quantity plane’: first, no close substitutes and second, that the cost of acquiring the marginal unit be small relative to the purchaser’s base of wealth. Both conditions apply and we advance these as the explanation for the result. For there were no immediate substitutes for UK population transfers in the sense that the natural increase of the resident Australian population took time, and historically, the increase via non UK transfers was small. In the case of southern Europeans, where the flow could have been very much larger, these migrants, as we saw, were not wanted; ironically it was this group who were to come to form the backbone of the immigration programme in the 1950s. The second condition is satisfied too, for the price or cost involved in offering subsidies was small relative to Australia’s total budget or wealth. This last point does not mean that the budget constraint ought to be insignificant, for although outlays on subsidies were a small part of Australia’s budget, when funds for ventures were cut back by treasurers, their blades could and in fact did fall upon both big and small outlays.23 Finally on the subject of M , it should perhaps be stressed that the ability of governments to affect the number of arrivals by varying SPAdepended upon supply being responsive to changes in subsidies (and transport costs). Govern- ment ability to affect numbers was not impaired by demand being inelastic.

Though not reported in Table I1 our proxy for defence needs, DEF, systematically failed the ‘t’ test. It would be premature, however, to conclude that Australians did not see immigration as an aid, in some form, in the defence of Australia against what was called at that time the ‘Yellow Peril’. Rather, the result might owe more to measurement problems with the proxy for the community’s fears, or it might be that negative substitution effects between migrants and armaments offset the positive effects of the ‘threat’ upon the demand for UK migrants. The other possibility is that the perceived threat though present did not vary much over time, however, estimates of the constant term were insignificant and close to zer0.2~

b. 2SLS Estimation Our estimates of the population equations most probably suffer from some simultan-

eity bias. The endogenous variables in the model are, it will be recalled, M , S P A , N WA and U A . The question is whether the biases in estimating the pair of equations Ms, SPAidby OLS are greater than the errors involved in two stage estimation proce- dures. The problems we have encountered in 2SLS estimation cause us to place the weight of our emphasis upon the OLS method.

These problems are the statistically unreliable estimated coefficients of the reduced form equations and the simplifications, especially in the inverse demand relation, that had to be imposed to reduce nonlinearities in the s stem in order to use the two stage

ion,25 that M and EMC (hence U A ) were linearly related (this last specification run- method. The necessary assumptions were that N W 1 was set in a Wold recursive fash-

23There is a good deal of evidence in the records of budgeting considerations impinging on immigration

24This is not conclusive insofar as some unspecified constant force may have countervailed this effect. 2JGiven the sequence of events in institutional wage fixing (identifying guidelines, investigating

unemployment and price movements then determining wages), such an assumption is quite reasonable.

[see 8 and 41.


TABLE I11 Migrant ~ u p p ~ y t t (ZSLS)

-A 12

-B 12

.69 -A 13

-B 13

-A 14

-B 14

(6.63)***

.40 (I.S8)*

.s4 (3.79)** *

.39 (1.39)*

- .01 (- .04)

- .07 (-1.21)

- .I3 (-1.39)*

- .06 (- .96)

- .os (- .47)

- .04 (- .SS)

- .67 (-3.60)***

- .I0 (- .38)

- .2s (-1.34)*

.os ( ,211

- .os (- .26)

- .33 (-2.18)***

- .s7 (-S.68)***

- .43 (-4.01)***

- .s3 (-3.24)***

- .49 (-3.17)***

.I9 t .6S .S7 .S9 (1.12)

.21 t .S7 .44 1.54 .80 (2.04)

.31 t .84 .61 1.21 (2.60)

.I9 t .61 .47 1.54 .70 (2.02)

.80 .62 1.09

.S1 .40 1.40 .70

TABLE IV Inverse Demandtt (ZSLS)

Equation IF 0: BC, T Mt R2 @ D W p

-A 15 .25 t 2.18 (1.66) (6.41)***

.07 t 2.15 -B 1s

- A 16

-B 16

( .80) (3.50)***

1.31 .38 t (6.80)*** (2.40)

1.22 .09 t (3.80)*** (1.01)

-1.68 (-4.63)***

-1.06 (-2.54)***

- .64 (-3.10)***

(- .14) - .04

-.I0 .81 .64 .92 (438)

-.04 .S4 .43 1.32 1.00 (-.72)

-.04 .82 .63 1.08 (-.33)

-.02 .S6 .43 1.62 1.00 (-.3S)

Notes to Tables III and IV

t t regressions exclude 1914-19 t coefficient has wrong sign

( ) t statistics are in parentheses below estimated regression coefficients significant at ten per cent level (one tail test)

** significant at five per cent level (one tail test) *** significant at one per cent level (one tail test) wb distributed lag weights of

W O = ~ , U - I =.67 ,~-2=.33 All regression equations were run with and without a constant term. As in no instance was the term remotely significant only equations omitting the term are reported above. However, in order to avoid bias in the ‘goodness of fit’ statistic, the reported R* and R2 were computed for the regressions inclusive of the constant term.


ning counter to historical evidence of government response patterns), and that employers were insensitive to the output price/labour cost ratio. A less offensive but further assumption was that U A could be treated as a predetermined variable in RSCand TC. Even so, one intractable nonlinearity remained in the system.26

The results of re-estimating the structural equations are reported in Tables I11 and IV. In the supply function, after correcting for serial correlation, income differences and search cbsts were significant, though M A L retained its perverse sign. Transport costs inclusive of the simultaneous effects of Mand hence SP TC(designated T e ) appeared insignificant; nor did lagged transport costs prove significant when included alongside. That transport costs proved insignificant in any form is contrary to apriori reasoning and earlier tests, and is most probably to be explained by the statistically unreliable reduced form coefficients.

The inverse demand function includes the effects of Mand S P A on the union and employer pressure group variable, EMC (designated oA) and the effects of S P A on M(designated @. The other variables included are public investment, I G the budget constraint, BC, and the dummy, T. Our previous conclusions with regard to the impact of the last three generally hold and need not be elaborated: they retain their importance as determinants. Nor in light of our comments on the significance of the ‘own price-quantity plane’ is the insignificance of fi surprising. But 0 proved insignificant and its sign was contrary to all considerations.

In summary then, the ZSLS estimates reinforce most of the conclusions reached earlier. Where they differed from the OLSestimates, concerning the effect of transport costs on supply and of unemployment on demand, the OLS estimates are far more plausible. This coupled with the problems enumerated at the beginning of this section which cause the ZSLS to be somewhat unreliable, mean that the OLS estimates form our preferred equation set, and it is upon these that our concluding remarks are based.

V. CONCLUSIONS

Australia wanted more people. But no-one, not even Australia’s optimistic Prime Minister, Billy Hughes, thought that a more optimal distribution of population could be achieved at short notice. Hughes’ own time horizon was of the order of twenty years and with him most, until perhaps the depression of the 1930s, agreed.

The demand for population additions from the United Kingdom which would set a path towards some long term optimum was largely a function of short term economic factors. Our results show that as Australian public investment rose and as the budget constraint eased (both of these were fattened on foreign borrowing), so the demand for

26This entered via the term ( UA. M). In the labour market the ex antelexposf translation of excess dem- and for migrant labour implied MLd< MLS by the total numbers unemployed, i.e. UA( W + A . M). Tak- ing UA through the bracketsyields theterm, &(A. M). But UA and Mareendogenous. Asaresult, two stage linear regression packages could not be used. We first derived the reduced form equations, then used predicted values of the endogenous variables as instrumental variables in the second stage. As already mentioned the reduced form coefficients were all insignificant. The equations comprised conglomerate terms which could not be unscrambled and interpreted with meaning.


peopling Australia increased. At the same time governments took into account the impact of new arrivals upon the domestic labour market and as the labour market tightened, average subsidies rose and vice versa. Our estimates of mapping price against quantity revealed this demand relation to be negatively sloped as expected, though insignificant, which is seen to reflect the absence of close substitutes for United Kingdom migrants and the comparatively small size of the outlays involved, relative to Australia’s total spending power. The budget constraint on immigration was nonetheless an important consideration as Treasury cutbacks were not only reserved for the bigger government outlays. Finally, our results show an inward shift in the SPAidfunction in the 1920s which is interpreted as reflecting increasing concern after the war with the market prospects for traded goods produced by an expanding population. This, ceterisparibus, dampened enthusiasm for more immigrants and lowered Australia’s average subsidy payment to migrants: such an effect seems to have been strong for at the same time the Australian Tariff was most probably shifting the demand for migrants outwards. The combined influences of all these variables account for 80 per cent of year to year variation in Australia’s demand (over two-thirds of the variance).*’

As to why UK migrants came to Australia, at least three influences on annual variation in the inflow have been detected: expected income gains, transport costs and the costs of job search. Of these three variables one, transport costs, had not been previously investigated by researchers, while expected income gains which had, had been rejected in all studies of nineteenth and early twentieth century Australian immigration. Nor had search costs been explicitly estimated, where dealt with at all, these had been subsumed in the polyglot expression, ‘pull’. That the income difference was found to be significant might be attributed to the more careful specification ofthe relevant magnitudes. Our estimates of the supply function were in one respect perhaps less satisfactory than those of SPAid insofar as the combined variables accounted for about 75 per cent of the annual variation (60 per cent of the variance); thus more remains ‘unexplained‘ in the case of supply than demand.28

REFERENCES

1. Australian Archives Office, Prime Minister’s Department, Correspondence File, A458, P. 156/ 1, Part 111.

2. Australian Archives Office, Prime Minister’s Department, Correspondence File, “Immigration Encouragement. Main Policy File, 1919-1924”, CRS A458, item G154/7, Part I.

3. Australian Archives Office, Prime Minister’s Department, Correspondence File, “Passage Money Policy”, CRS A461, item A349/ 1 /4.

4. Australian Archives Office, Prime Minister’s Department, Correspondence File, “Immigration Encouragement, Expenditure, 1920-25”, CRS A458, item H 154/5.

5 . Australian Archives Office, Prime Minister’s Department, Correspondence File, “Money Agreements, British and Commonwealth Governments, 1922-27”, CRS A436, item 46/5/3718.

2’These percentages were calculated from the average value of R (and R2 respectively) for the set of equations reported in Table I1 corrected for serial correlation.

2RThese percentages were calculated from the average value of R (and R2 respectively) for the set of equations reported in Table I, which include lagged not current search costs and which are adjusted for serial correlation.

1981 MODELLING THE PEOPLING OF AUSTRALIA: 1900-1930 28 1

6.

7.

8.

9. 10. 11.

12.

13.

14.

15. 16.

17.

18.

19.

20. 21.

22.

23.

24.

25.

26.

Australian Archives Office, Prime Minister’s Department, Correspondence File, “Immigration Encouragement, Passage Money and Loans Policy, 1920-27”, CRS A461, item A349/ 1/4. Australian Archives Office, Prime Minister’s Department, Correspondence File, “Colonel Manning’s Report”, CRS, Al, item 32/7159. Australian Archives Office, Prime Minister’s Department, Correspondence File, “High Commissioner’s Office, Migration Branch, 1920-29”, CRS A461, item N348/1/8, Part I . Commonwealth Parliamentary Debates, 1922. Brian Fitzpatrick, The British Empire in Australia, (Melbourne: Melbourne University Press, 1949). Franklin Fisher, “Identifiability Criteria in Non-Linear Systems: A Further Note”, Econometrica, vol. 33, 1965. Belton Fleisher, “Some Aspects of Puerto Rican Migration to the United States”, Review of Economics and Statistics, vol. 45, 1963. Michael Greenwood, “An Analysis of the Determinants of Geographic Labour Mobility in the United States”, Review of Economic Statistics, vol. 5 1 , 1969. Neville Hicks, “Evidence and Contemporary Opinion about the Peopling of Australia, 1890-191 I”, Ph.D. thesis, Australian National University, 1971. Harry Jerome, Migration and Business Cycles, (New York: NBER, 1926). D. W. Jorgenson, “Anticipation and Investment Behaviour” in J.S. Duesenbury et. al., (Chicago: The Brooking Quarterly Econometric Model of the US, 1965). Allen C. Kelley, “International Migration and Economic Growth: Australia, 1865-1935”, Journalof Economic Hisiory, vol. 25, 1965. Phillip Nelson, “Migration, Real Income and Information”, Journal of Regional Science, Spring, 1959. David Pope, “Empire Migration to Canada, Australia and New Zealand, 1910-1929”, Australian Economic Papers, vol. 7, 1968. David Pope, “The Peopling of Austrlia”, Ph.D. thesis, Australian National University, June, 1976. David Pope, “The Push-Pull Model of Australian Migration”, Australian Economic History Review, vol. 16, 1976. David Pope, “The Contribution of United Kingdom Migrants to Australia’s Population and Economic Growth; Federation to the Great Depression”, Australian Economic Papers, vol. 16, 1977. David Pope, “Contours of Australian Immigration: 1901-30”, Australian Economic History Review, vol. 21, 1981. David Pope, “Assisted Immigration and Federal State Relations: 1901-30”, Australian Journal of Politics and History, forthcoming. H.W. Richardson, “Emigration and Overseas Investment, 1870-1914”, British Economic History Review“, February, 1972. Jeffrey Williamson, “Migration to the New World: Long Term Influences and Impact”, Explorations in Economic History, vol. VII, 4, 1974.


A PPENDI x A full description of the data including discussion of their construction and inadequacies is given in Pope

EMC, UA. Australia: Bureau of Census and Statistics, Labour Reports; N.G. Butlin, 'An Index of Engineering Unemployment, 1852-1943, Economic Record, December, 1946.

d, Q(a1so Chart I). Australia: Overseas Migration and Shipping and Demography Bulletins; for 1901-03 figures from State Statistical Registers.

N@. Australia: Bureau of Census and Statistics, Labour Reports, 1902-06 interpolated using an employment weighted average of Victorian and NSW money earnings in manufacturing taken from various sources.

SPA, SPuK, TC. Passage rates and subsidies issued by governments from State and Commonwealth Year Books and 'Estimates' and 'Financial Statements' in various Parliamentary Papers; also see [20, pp. 182- 247, 5041.

M . For most of the period from UK Board of Trade Journals and Annual Reports. Prior t o 1907 Australia was not recorded separately but combined with New Zealand as Australasia. These years have been interpolated using the UK inflow figures into Australia from Australian sources cited above.

RSC. See u 4 CPI A, NW ' K u ' K

RYD. See UiNWiCPIiHi; i=Australia, UK.

[201.

A L

UuK. B.R. Mitchell, Abstract of British Historical Statistics, (Cambridge: Cambridge University Press, 1962).

NWUK. A.L. Bowley, Wages and Income in the U K Since 1860(Cambridge: Cambridge University Press, 1937); 'Index Numbers of Wage Rates and the Cost of Living, Journal of Royal Statistical Society, 1952.

CPIuK. A.L. Bowley, Wages and Income in the UK Since 1860, op. cit.

HuK. M.A. Bienefeld, Working Hours in British Industry (London: London School of Economics Mono- graph, 1972); E. Phelps Brown and Margaret Browne, Century of Pay, (London: Macmillan, 1968).

CPI . Australia: Bureau of Census and Statistics, Labour Reports.

d. Australia: Bureau of Census and Statistics, Labour Reports. F. See sources for M; figures for years prior to 1901 from F.K. Crowley, 'British Migration to Australia: 1860-1914", D.Phil. thesis, Oxford, 1951.

0, n. Estimated from data in B.R. Mitchell, Abstract of British Historical Statistics, pp. 9-13.

AP, RGNP, NGNP, I , DGNP. N.G. Butlin, Australian Domestic Product. Investment and Foreign Borrowing, 1861-1938/39, (Cambridge: Cambridge University Press, 1962).

2. Commonwealth Budget, 1940 and [20, p. 5061.

A

G

Documents

MODELLING THE PEOPLING OF AUSTRALIA: 1900–1930