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University of Pisa

Scuola Superiore Sant’Anna

Department of Economics

Master of Science of Economics

Distribution of Wealth in Italy

before Second World War

Supervisor

:

Candidate

:

Davide Fiaschi

Giovanni Bonaccorsi

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Contents

1 Introduction 3

1.1 Putting wealth back at the center of the debate . . . 3

1.2 Outline of the thesis . . . 5

2 Wealth Accounting 7 2.1 The Definition of Wealth . . . 7

2.2 The Wealth Income Ratio . . . 9

2.2.1 Definition . . . 9

2.2.2 Dynamic Equation of The Wealth-Income Ratio . . . 10

2.2.3 The two laws of capital accumulation . . . 12

2.3 Wealth Ratios in The Period 1970-2010 . . . 13

2.4 Explaining Wealth Ratios in 1970-2010 . . . 18

2.4.1 Multiplicative Decomposition of Wealth . . . 18

2.4.2 Explaining the Germany puzzle . . . 20

2.5 Explaining Wealth Ratios in 1870-2010 . . . 22

2.6 Final Remarks . . . 26

3 Historical Estimates of Wealth 29 3.1 Accounts of Italian Wealth:1966-2011 . . . 29

3.2 Historical Estimates . . . 30

3.2.1 The Earlier Estimates . . . 30

3.2.2 Methodology of the Estimates . . . 31

3.2.3 The Debate on Multipliers . . . 33

3.2.4 Italian Wealth Estimates after 1908 . . . 38

3.3 Italian Wealth Series . . . 39

3.3.1 Retti-Marsani’s series for 1908-1934 . . . 39

3.3.2 Baffigi series for 1872-1913 . . . 42

3.4 Final Remarks . . . 45 1

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2 CONTENTS 4 Models of Distribution of Inheritance 47

4.1 Introduction . . . 47

4.1.1 Inheritance in the long run . . . 47

4.1.2 Main intuition . . . 48

4.1.3 Accounting of Bequested Wealth . . . 49

4.1.4 Demography, Production, Government . . . 50

4.2 Indirect savings formulation . . . 51

4.2.1 Indirect savings models: class savings . . . 51

4.2.2 Indirect savings models: generic savings . . . 54

4.2.3 Indirect savings models : Open economy . . . 57

4.3 Direct Savings Formulation . . . 61

4.3.1 Direct savings models : dynastic model . . . 61

4.3.2 Direct savings models : Wealth-in-the-utility model . . . 69

4.4 Conclusions on model of bequest accumulation . . . 75

4.5 Wealth distribution shape . . . 76

5 Wealth in 1927 81 5.1 Introduction . . . 81

5.2 Methodology and sources followed by Piketty . . . 82

5.2.1 Data sources . . . 83

5.2.2 Methodology for direct measures of bequest . . . 85

5.2.3 Methodology for indirect measures of bequest . . . 89

5.3 Piketty’s results . . . 93

5.3.1 Decomposition of the bequest-income flows . . . 93

5.3.2 Conclusions . . . 97

5.4 Methodology for wealth distribution estimates in 1927 . . . 97

5.4.1 Data source . . . 98

5.4.2 Methodology to obtain a wealth distribution . . . 99

5.5 Results . . . 106

6 Conclusions 111

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Chapter 1

Introduction

1.1

Putting wealth back at the center of the debate

The distribution of wealth is a topic which is not always extensively discussed in macroeconomic courses nowadays. The big question has always been the difference in levels of income per capita, which was often explained by different accumulation mechanism. One of these mechanisms indeed, as the classic Solow model highlighted, regarded wealth, but only in the form of capital in the production function, hence focusing only on wealth which was accumulated through investment.

In a different manner redistributive claims in the public debate have involved income and also wealth as source of inequality (the "1% movement" for instance). But, while distribution of income has always been linked with processes of produc-tion and repayment of factors, wealth on the other side had a more wide definiproduc-tion which included also forms of wealth not directly linked with the capitalistic organi-zation of factors. If on one side the theory of maximiorgani-zation of profits led the debate to focus on the capital and labor share of output, on the other side it has never been clear which was the degree of similarity among wealth and capital, hence if concentration of wealth has to be judged as bad as increasing capital intensity .

Finally, data for wealth have been missing for a long time, since national accounts have started to be pubblished only in the last twenty years. While wealth estimation was a very common topic for economists in 19th century, in the next

century the more relevant economic measure became income, slowing down the 3

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4 CHAPTER 1. INTRODUCTION interest and the effort in collecting wealth data.

In the last years the work of Thomas Piketty has helped to shed light the path and the processes underlying wealth concentration in developed countries and has put the wealth issue back at the center of the debate. Firstly a consistent database of wealth measurements has been built, which comprehends both national accounts and historical estimates. Then Piketty has tried to explain those measures through a theory of wealth accumulation and concentration, with clear testable implications and consistent with available economic theory. Finally, the consequences of this theory have been exploited, leading to some advices for public policy and fostering the public debate on the issue of wealth concentration. The culmination of this process has been the publication of the book “Capital in The Twenty First Century”, which has tried to explain these theories about wealth to the largest possible public. The picture we obtain by the work of Piketty is that accumulated wealth is increasing over time if institutional or external causes do not affect its pattern. Since wealth tends to remain concentrated in the hands of few people, without a specific merit from its owners, this might be a major source of unfair inequality in society. By consequence public policy is needed in order to regulate this behavior.

Anyway this line of research calls for further development in different directions. First, some of these claims are empirically verified in a sample of highly significant countries: the sample needs to be expanded both in time, with historical estimates, and in space with further national accounts. Secondly further theories of wealth accumulation may explain the actual landscape too, hence it should be verified if better explanations are available. Thirdly, this wealth theory relies on a series of assumptions and reasoned approximations, which need to be carefully weighed up and verified. Finally, while revealing a wealth landscape where wealth levels are comparable with ones of the early years of the 19th century, it is still not clear the real concentration of wealth. Since now the studies have confirmed that wealth continues to be as concentrated as in the past, if not more, but these claims need more reliable sources in order to be solid. Nevertheless they picture a worrying situation, where wealth inequality has not changed from the past.

Following the framework identified by Piketty I have tried to build a reference point for wealth in Italy, before World War II in order to figure out the picture of wealth accumulation in Italy. I have built a cross section of bequested estate

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1.2. OUTLINE OF THE THESIS 5 commodities for the year 1927 which I have derived from one of the publications of the Italian Treasury ("Bollettino di Statistica Comparata"). Then I have tried to use it in order to estimate the whole amount of wealth in Italy, by using the devolutive interval method, and with the results I’ve calculated the concentration of wealth in the country. This work should help to test the claim on wealth accumulation pattern in Italy in the 20th century and to verify how the new dataset is compliant with previous estimates and measures of wealth.

1.2

Outline of the thesis

The work is structured as follows.

In Chapter 2, I start by briefly reviewing some of the recent literature about wealth, highlighting the recent works of Piketty and of his colleagues. I will highlight both the basic theoretical framework on wealth accounting and the empirical wealth patters in different countries, in the period 1970-2010.

I’ll then move in Chapter 3 on the issue of historical estimates, focusing in particular on the Italian case and reviewing briefly wealth series for most of the years before 1970.

After that, in Chapter 4, I’ll expose a few different models of inheritance accumulation, with the aim to find a theoretical model coherent with empirical findings. I’ll then continue by highlighting how in these models the shape of wealth distribution could emerge.

Finally, in Chapter 5, I’ll proceed to explain the methodology necessary to exploit bequest data, comparing the results obtained by Piketty with those obtained by me with the new data collected and highlighting the difference in methods and data source which I have encountered in my work.

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Chapter 2

Wealth Accounting

2.1

The Definition of Wealth

National wealth is defined as the sum of private and government net wealth of a certain country:

Wnt = Wt+ Wgt

Net wealth means the total sum of the assets, which provide economic benefits for their owners, minus total sum of liabilities. These represent both financial and non financial assets upon which ownership rights can be enforced.

For the private sector, composed by households and nonprofit institutions serving households (NPISH), some remarks must be made. Firstly, claims on future government expenditure, such as social security pension wealth of the PAYG type, are excluded. Durable goods too, since their measurement is aleatory, and their relevance is small. Finally human capital is not accounted since there are no property rights which can be enforced on human beings and, moreover, including human capital would be challenging for the whole definition of capital and this exit from the scope of wealth accounting.

Usually evaluation takes place at market prices, including corporations through market value of their equities and bonds for those which are quoted, using compa-rable public companies for those unquoted.

Equally public wealth represents net wealth of public administrations, which, differently from private wealth, is usually valued by cumulating past investments

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8 CHAPTER 2. WEALTH ACCOUNTING and upgrading the results with respect to changes in real estate prices.

There are other decomposition of wealth that can be made. First, wealth can be seen as the sum of domestic capital and net foreign assets. Net foreign assets represent the difference among the total share of foreign states wealth owned by domestic citizens and the total share of domestic wealth owned by foreign citizens. Domestic capital then, can be decomposed in different types of capital: agricultural land, housing and capital of other types (which includes the value of corporations and other non-financial items):

Wnt = Kt+ N F At= KAt + KHt + KOt+ N F At

Secondly corporation wealth can be evaluated at book value, rather than with market value of equities. If evaluations differ (technically: if Tobin’s Q is different from 1), whatever the motivation is, a residual corporate wealth is produced; hence we can now define book value wealth as: Wbt = Wnt + Wct.

The measurement of wealth follows standard methods which have been formal-ized by the System of National Accounts (SNA) of United Nations. These methods are collected in two series of international guidelines, published in 1993 and 2008, to which official national accounts must comply in order to ensure comparable balance sheets. This balance sheets are now available for the years 1970-2010 for a representative sample of developed countries and are the fundamental source of data which has been exploited by Piketty in his work. The particular feature which makes this accounts so valuable is the method mainly used to measure wealth, which is the census method, as opposed to the perpetual inventory method.

The perpetual inventory method tries to estimate the value of wealth by approximation, cumulating past investment flows and adjusting for price changes. This method works fine if balance sheet data are not available and wealth is not directly observable, but suffers of a series of flaws which one would like to avoid in order to estimate wealth. Those flaws are absent from the census method, which relies on direct report of wealth, at current market prices. Financial wealth is obtained from balances of financial institutions. Those report can be both from internal balance sheet and from off-balance sheet of values which the institutions are managing or simply taking into custody. Real estate wealth is instead obtained

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2.2. THE WEALTH INCOME RATIO 9 by censuses of built areas and by observation of transaction prices. By consequence there are four main advantages of census method. First, the inclusion of non-produced assets (land for instance), which is not affected by investment and hence ignored by PIM. Second the avoidance of estimation of prices, which makes PIM unreliable and hard to carry out. Third the inclusion of intangible capital, via the value of equities of corporation, otherwise absent. Finally the standardization of measurement, which follows from the SNA guidelines. These are the advantages which make the new data sources and improvement with respect to old methods (carried on for instance, in order to test the Solow model). At the same time they’re not perfect, in particular they suffer from a major pitfall which comes from unreported wealth. Indeed those balances do not capture wealth stocked in tax havens which rarely make reports. This must be taken into account and the figure one can obtain from balance sheet must be interpreted as a lower estimate. The amount of unreported wealth can then be estimated to update the results of the census method, but I will just report the estimates made from other scholars. There’s at least one case where the perpetual inventory method represents a valid alternative to wealth census, it is the case of assets other than financial claims and real estate, hence of corporate tangible assets, whose market value cannot be directly observed. But, since the value of corporations is taken as the market value of their equities, PIM can be avoided even in this case.

2.2

The Wealth Income Ratio

2.2.1

Definition

The particular measure of wealth which is interesting to focus on is the ratio of wealth and income. Net income is defined as the sum of net domestic output, which can be seen as the outcome of an aggregate production function, and net foreign income:

Yt = Ydt + rtN F At= F (Kt, Lt) + rtN F A

The more relevant ratios are the private wealth - national income ratio, βt= WYtt,

and the national wealth - national income ratio, βnt =

Wnt

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10 CHAPTER 2. WEALTH ACCOUNTING that if the economy is closed, hence if N F At= 0, then βnt = βkt =

Kt

Ydt, which is

the domestic capital-domestic output ratio. Finally, if also government wealth is reduced to 0, then private wealth and national wealth are the same thing, hence βt= βnt = βkt.

It is also interesting to see how β is related to another common variable of interest for macroeconomic theory: the capital share α. By definition: α = rtKYtt = rtβkt

where rt is the average rate of return of domestic capital, which is equal to the

marginal product of capital if we assume perfect capital markets. With closed economy and a Cobb-Douglas production function, α is a constant, hence rt and

βkt compensate each other. If otherwise economy is open, the previous statement

is true at a world level, while more wealth endowed countries should invest abroad, and vice versa for the less endowed. Finally if production is modeled by a constant elasticity of substitution function, the capital share would be an increasing function of βkt if elasticity of substitution among capital and labor, σ, is greater than one.

Hence if the ratio rises, r falls but proportionally less than the rise of βkt , due to

the high substitutability of labor and capital, hence the capital intensity increase as a result. The vice versa happens if σ is less than one.

2.2.2

Dynamic Equation of The Wealth-Income Ratio

We can decompose national wealth accumulation during time in a volume effect, due to net savings among two periods, and in a price effect, due to capital gains or losses in the same time interval.

Wnt+1 = Wnt + St+ Gt

The relative price effect is absent if we look at a model with only one wealth good. Then the dynamic equation of the national wealth-national income ratio can be derived as follows: βnt+1 = Wnt+1 Yt+1 = Wnt + St Yt+1 = Wnt + St Yt Yt Yt+1 = βnt(1 + st βnt) 1 + gt = 1 + gwst 1 + gt βnt

Where at the numerator we can find wealth growth rate induced by savings and at the denominator national income growth rate. In the long run, given fixed rates s

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2.2. THE WEALTH INCOME RATIO 11 and g, the steady state ratio becomes:

βn = 1 + s βn 1 + g βn⇒ 1 + g = 1 + s βn ⇒ βn = s g

This simple formula represents a pure accounting equation, in the sense that it is always true at the steady state of any microfounded economic model, independently from the motivation of savings. It is the well-known Harrod-Domar-Solow formula and it?s the outcome of the following simple model.

Assume production is represented by a Cobb-Douglas production function of the type Yt= KtαH

1−α

t where H represent efficient human capital. Assume moreover

that we are in a closed economy without taxation, hence wealth and capital perfectly overlap,Kt= Wt, and move as follows:

Kt+1= Wt+1= Wt(1 − δ) + St= Wt(1 − δ) + sYt= Wt(1 − δ) + [sLYtL+ sKYtK]

Here we can see that gross wealth at period t + 1 is the result of the accumulation, in period t, of wealth net-of-depreciation and savings (which in this case are a constant share s of income). Assuming perfect competition we can exploit Euler law for the division of output and then apply the definition of capital share:

Wt+1 Wt = (1 − δ) + [sL(1 − α)Yt+ sKαYt] 1 Wt = (1 − δ) + [sL(1 − α) + sKα] rt α Finally we can look at the growth rate of income in equilibrium:

Yt+1 Yt !eq = " Kt+1α (1 + g)t+1Lt+1 Kα t(1 + g)tLt # = (1 + g)(1 + n)

The standard condition for equilibrium is that capital and income must grow at the same rate, hence the above dynamic equations must be equal in equilibrium. Remembering the definition of α and recognizing that seqt = sL(1 − α) + sKα we

get:

(1 − δ) + seqt rt

α = (1 + g)(1 + n) = 1 + g + n + gn ⇒ −δ + seqt

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12 CHAPTER 2. WEALTH ACCOUNTING

βteq= s

eq t

g + δ + n + gn

The final equation is the extended version of of Harrod-Domar-Solow condition which was showed before. If we simplify the analysis, observing net wealth only (δ = 0), and if we assume that population growth is stagnating (n ≈ 0) and the interaction among population and income is irrelevant ( gn = 0), then the equation is reduced to the previous one: β = sg.

2.2.3

The two laws of capital accumulation

The aforementioned equations play an important role for Piketty in order to grasp the dynamic of wealth accumulation. In his best-seller book, “The Capital in The 21st century”, he used them as the main tools to explain most of the

concepts about wealth (which he defines generically as “capital”) and names them as “fundamental laws”: 1. First law: αt= βtrt 2. Second law: βt= st gt

As we said before these are identities, which tends to self fulfill in every theoretical model. In particular the first rule comes directly from the definition of capital share in output and we expect it to be empirically true in every moment of time. Moreover, it relates the wealth-income ratio, which since now has been an accounting concept solely, with one of the most discussed variable of macroeconomics, hence highlighting the explaining power of β .

On the contrary the second law is not expected to be true in every moment of time, but only in the long run. Indeed, as I have showed before, it is the outcome of a model where imperfection in markets and fluctuation in prices of capital goods are avoided and this, obviously, cannot be true in the short run. Nevertheless, this law describe pretty well the dynamic of wealth accumulation, demonstrating its usefulness in order catch the determinants of the wealth-income ratio. As I’m going

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2.3. WEALTH RATIOS IN THE PERIOD 1970-2010 13 βwt βt β1970 β2010 β1970 β2010 U.S 342% 410% 404% 431% Japan 299% 601% 359% 616% Germany 225% 412% 313% 416% France 310% 575% 351% 605% U.K 306% 522% 314% 523% Italy 239% 676% 259% 609%

Table 2.1: Private Wealth-National Income ratio (βwt) and National Wealth - National Income ratio (βt) for the periods 1970 and 2010.

to show briefly, it happens to be a precise predictor of the behavior of β for the long run of the sample (period 1860-2010), while for the short run it will only be necessary to vary it slightly in order to account for capital gains and losses and other measurement errors.

2.3

Wealth Ratios in The Period 1970-2010

In order to have a brief overview of the behavior of wealth ratios in the period 1970-2010, I report in Table 2.1 the results for the extremes of the period. The values are taken from the Data Appendix of Piketty-Zucman 2013, which reports calculation made directly from national accounts.

As we can see from the table, wealth ratios have increased in the whole period for each of the country of the sample we are looking at, moreover if we’d looked at wealth-disposable income ratio those figure would have jumped up, since the latter is always lower than income per se. In order to comment properly the evolution of those countries it is necessary to look at the yearly amount of the ratios for the whole period. I plot those ratios in Figure 2.1.

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14 CHAPTER 2. WEALTH ACCOUNTING ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 200 300 400 500 600 700 Years Pr iv ate W

ealth − National Income Ratio

1970 1980 1990 2000 2010 ● ● USA Japan Germany France UK Italy ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Figure 2.1: Private Wealth - National Income Ratios for the years 1970-2010

As one can see all the countries in the sample had an increase in the private wealth ratio, with a wide variance though. While at the start of the sample each of them was comprised in the range 200-300%, at the end of the 40 years period we can observe a range from 410-412% (USA and Germany) to 601-676% (Japan and Italy). Italy indeed is the most wealth endowed at the end, while Japan reached the highest values of the ratio in our sample in 1990, with the Japanese asset price bubble. In the more recent years we can see how the crisis affected wealth in those countries: the major inflection has taken place in the USA, while in other countries the variation has been little or absent. Finally it is worth noting the performance of Germany, which starts from having roughly the same initial level of Italy, to be the least endowed in wealth in the sample. This behavior, which indeed seems unlikely, will need some further explanations.

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2.3. WEALTH RATIOS IN THE PERIOD 1970-2010 15 increase in the percentage in all the countries except for Italy. As a matter of fact, government wealth (which is the difference between national and private wealth) has decreased in all the sample. To see this, I plot in Figure 2.2 the government wealth - national income ratio, for the same time span and the same countries.

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● −50 0 50 100 Years Go v. W

ealth − National Income Ratio

1970 1980 1990 2000 2010 ● ● USA Japan Germany France UK Italy ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Figure 2.2: Government Wealth - National Income Ratios for the years 1970-2010

There is a clear downward trend for all the countries of the sample, which moved from above 50% in the ‘80s to near 0 in the last years. In particular Japan behavior has been different from others in the years after 1990, with a government wealth-national income ratio still high, but has then reduced rapidly its gap. Finally Italy has again a totally different shape, with a negative ratio starting from 1980 and getting worse in years after.

Nevertheless the whole effect on national wealth of this downward trend is not really relevant: the increase of private wealth in the period has been so high that the decrease in national wealth is rarely noticed, as one can see from Table 2.1. Generally national wealth is some percentage points greater than private wealth,

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16 CHAPTER 2. WEALTH ACCOUNTING with the notable exception of Italy, which though remains the second most wealth endowed, at a national level, of the sample.

There’s one last decomposition which is necessary to conclude this qualitative overview of data, that is the decomposition of national wealth in its domestic and foreign component. In Figure 2.3 I plotted the foreign component.

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● −20 0 20 40 60 Years Domestic/F oreign W

ealth − National Income Ratio (%)

1970 1980 1990 2000 2010 ● ● USA Japan Germany France UK Italy ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Figure 2.3: Foreign Wealth - National Income Ratios for the years 1970-2010

It is immediate to recognize two group of countries: one with a substantial positive share of net foreign assets in their national wealth, which are Japan and Germany; another with a negative share, which hence will have a domestic capital-national income ratio higher than capital-national wealth one. Moreover one can see that this divergence has started only recently, in the second half of the eighties, while before each countries had a roughly positive share. Finally, France has joined the second group only in the first years of 2000.

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2.3. WEALTH RATIOS IN THE PERIOD 1970-2010 17 βnt βkt K+N F A Y K Y N F A Y KH Y K−KH Y US 1970 404 399 4 142 257 2010 431 456 -25 182 274 var. 27 57 -30 41 17 Japan 1970 359 356 3 131 225 2010 616 548 67 220 328 var. 256 192 64 89 103 Germany 1970 313 305 8 129 177 2010 416 377 39 241 136 var. 102 71 31 112 -41 France 1970 351 340 11 104 236 2010 605 618 -13 371 247 var. 254 278 -24 267 11 UK 1970 365 359 6 98 261 2010 527 548 -20 300 248 var. 163 189 -26 202 -13 Italy 1970 259 247 12 107 141 2010 609 640 -31 386 254 var. 350 392 -42 279 113

Table 2.2: Decomposition of National Wealth - National Income Ratio(βnt) in its domestic and foreign components (Kt and N F At). Then decomposition of the Domestic Capital-National Income Ratio (βkt) in its housing (KH) and other forms of capital components. Periods 1970 and 2010.

I report in Table 2.2, the changes in the ratios, decomposed in the foreign assets, housing and other form components.

Again we can see that there’s a wide variance in the relative contribution of housing capital. There are countries where housing capital represents the bulk of the increase in the period 1970-2010, like in France, UK and Germany; while for other countries there’s a significant share also of other type of capital which contributes to the increase of βnt. For instance other capitals have a share in the

increase of βnt of roughly half of housing ones in US and Italy, and a share greater

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18 CHAPTER 2. WEALTH ACCOUNTING

2.4

Explaining Wealth Ratios in 1970-2010

2.4.1

Multiplicative Decomposition of Wealth

Previously I showed how the second law of accumulation of capital, as dubbed by Piketty, was easy to recover from a basic growth model or by looking at an accumulation equation for wealth which assumed no capital gains or losses. To effectively show how this law can predict movement in wealth ratio, we must introduce those price variations which we assumed before to be equal to 0. Moreover, the way we should account for those variations must also change from an addictive way to a multiplicative one: this method is necessary if we would like to measure other type of variations, different from capital prices ones. Hence, the accumulation equation of wealth, now is the following one:

Wt+1 = (1 + qt+1)(Wt+ stYt) = (1 + qt+1)(1 + stWYtt)Wt= (1 + qt+1)(1 + gwst+1)Wt

With gwst+1=st

βt equal to the wealth growth rate fostered by savings and qt+1 equal

to the growth rate of wealth coming from capital gains. If the term qt+1 is not

directly measured but obtained as a remainder of the other variables, hence by calculating the part of real growth rate of wealth unexplained by savings, clearly it will contains every other possible unmeasured errors of calculation or accounting, for instance in reporting savings or investment. This is the path followed in this case.

It is straightforward to move from the accumulation equation of wealth to the one of the wealth ratio simply by dividing by Yt+1:

βt+1=

(1 + qt+1)(1 + gwst+1)

1 + gt+1

βt

Now, having the time series of income, wealth and savings from national accounts one can easily reconstruct the necessary ratios and check if the law of accumulation, as here modified, is a good explanation of observed patterns. As a summary of this inquiry it is possible to define three type indicators. First the share of total wealth coming from savings: gwst

gwst+qt, and by complementarity the share of total wealth

coming from capital gains: qt

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2.4. EXPLAINING WEALTH RATIOS IN 1970-2010 19 of wealth has affected the final level: since accumulation move through savings, this could take time to show consistent results, then initial wealth should have a role on final wealth; at the same time economic growth affects savings, hence reducing the effect of initial wealth. To see this one can define the following shares: the share of total growth coming from initial wealth: βini

βt+n =

βt

βt+n(1+g)n; and share of total

growth coming from other variables: (1 − βini

βt+n)(

gwst gwst+qt +

qt

gwst+qt). The result of the

decomposition in volume effects coming from savings and price effects coming from capital gains can be seen in Table 2.3.

gw gws q gwsgws+q gwsq+q U.S. 3,0 2,1 0,8 72% 28% Japan 3,9 3,1 0,8 78% 22% Germany 2,7 3,1 -0,4 114% -14% France 3,6 2,7 0,9 75% 25% U.K. 3,5 1,5 2,0 42% 58% Italy 4,1 2,6 1,5 63% 37%

Table 2.3: Decomposition of real growth rate of national wealth(gw) in its savings and

capital gain components (gws and q) with relative shares. Periods 1970 and 2010, the

growth rates are averages.

As one can see in the majority of countries the bulk of wealth growth is due to savings: they account for about three quarters of the growth in U.S., Japan and France. For U.K and Italy instead capital gains have a larger share, between 40-60%. Finally Germany has a behavior totally different from the others with negative capital gains, in average, during the whole period.

It is now necessary to specify in a certain way, how those capital gains could be originated. Indeed, as I said before, the actual formulation may capture other measurement errors, and this may be caused in particular by two issues.

The first issue may be due to savings, which could be underestimated. In fact the NSA have only recently introduced some rules of accounting for R&D expenditures , which have been implemented only by Australia so far. Hence R&D expenditures may have been under-reported in saving accounts and their share should be corrected to fix this issue. Anyway, even adding a generous share of R&D expenditure to savings of all countries, by using observable shares of countries

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20 CHAPTER 2. WEALTH ACCOUNTING which reported them, the picture does not change a lot: according to modified savings the wealth at the end of 1970-2010 should be lower than the one observed. Hence there’s space for other type of capital gains

The second issue affecting the calculation of capital gains is due to capital gains obtained by privatization of public assets. If the sell price of public capital goods is cheaper than their real value than this will imply a capital gain for the household sector. As a matter of fact the operation should not change the total value of capital at a national level, being a pure transfer from one hand to another; hence the capital gain should be neutralized by raising the previous value of the public good (which was reported undervalued). Even by trying to consider this possibility, which is difficult to check by government accounts, the above decomposition remains valid as explanation.

2.4.2

Explaining the Germany puzzle

Even accounting for errors of measurement cannot explain why Germany should have a performance so different from the other countries of the panel. In order to formulate some hypothesis on the causes of this behavior I introduce a further decomposition of capital gains in their domestic and foreign component .

βKG Domestic share Foreign share

(%) (%) (%) U.S. 105 72 33 Japan 27 45 -18 Germany -25 -3 -22 France 164 179 -15 U.K. 235 217 18 Italy 213 240 -27

Table 2.4: Percentage decomposition of capital gain - national income ratio(βKG) in its

domestic and foreign components. Periods 1970 and 2010.

As we can see, while capital gains on foreign wealth have been both positive and negative in every countries, those on domestic wealth are negative only for Germany.

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2.4. EXPLAINING WEALTH RATIOS IN 1970-2010 21 The first thing it is necessary to explain is what is the cause of the great difference in domestic capital gains in the sample, then make some assumption on why this has not affected Germany. To achieve that it’s necessary to note that, in postwar years, capital gains of European countries mostly have been caused by asset price recovery. After the destruction caused by wars and the interventionist politics used by European states to foster the restart of the economy, the prices of capital goods started to rise. Housing in particular was affected by this reprise and it’s not a coincidence that the countries most endowed with housing capital had such great domestic capital gains.

Hence the enormous increase in capital gains of some countries can be explained by two things mostly. First there may have been some sort of “over-shooting” in the reprise of prices, which may have caused an increase in the value of assets over the real value of them. This in particular is represented by high real estate prices. Second, in those countries savings where high enough to generate an increase in the wealth-income ratio. Looking at the steady state formula β = gs, we can see that, with increasing savings and stagnating growth rate of income, the ratio should have raised in time. Moreover it is possible that those high savings could have been invested only in home country, due to a strong preference for domestic assets, hence causing a rise in domestic asset prices. It’s worth noting that this two motivations do not exclude one each other, hence the real cause may be a mixture of them.

Then, moving on why those phenomenon have not affected Germany, one can make different hypothesis. First it may be that German statisticians have overestimated savings or underestimate the actual stock of wealth. Secondly the recovery in prices may have been curbed by legal constraints in place in Germany, for instance rent control and the share ownership model of German corporation which may have reduced the market value of firms. Thirdly, saving tastes of German people may lean toward less expensive capital goods, in housing for example. Finally the phenomenon may not be an exception but rather a normal behavior if looked by the continental point of view. Indeed, if one calculate average capital gain of Europe, the German exception disappears and the picture look similar to the American one. Hence one can imagine these difference in capital gains as part of a common dynamic in capital gain, with negative effect on certain regional zones and positive effective on others. If data on U.S could be available on regional basis,

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22 CHAPTER 2. WEALTH ACCOUNTING this hypothesis may be tested.

To conclude: given the actual state of the data, the relative effect of these different explanations cannot be measured, hence one must resort to qualitative observations and hope for further development.

One last point should be made about foreign wealth. From Table 2.4 one can see that for some countries foreign wealth represent a significant share of capital gains. This happens for U.S, Japan and Germany itself. The motive why foreign wealth has such a weight in the decomposition is due to the increase in gross foreign position of the majority of countries: in time a greater share of domestic capital is owned by foreigner and a greater share of citizens own foreign capitals. This gross positions are mostly equivalent, as we saw with net foreign asset - national income ratio, but as a matter of fact obeys different laws and this affect greatly capital gains. Even if one country owns a share of foreign wealth which is roughly equal to the share of domestic wealth owned by foreigners, a differential in returns may foster capital gains or reduce them.

2.5

Explaining Wealth Ratios in 1870-2010

The previous analysis has shown how in the year span 1970-2010 decomposing wealth ratio dynamics could lead to some interesting explanation on determinants of wealth accumulation: both volume effects and price effects have demonstrated to be important for our analysis, hence highlighting how short run variance in capital prices (and measurement errors) should be taken into account in order to explain actual wealth ratio with respect to 1970 ones. One would like to expand this analysis to the period before 1970, to test the robustness of the assumption made since now and, if necessary, adjust them. To do this. some limitations in data must be considered: national accounts for periods longer than 1970-2010 are available only for four countries and are based on decennial estimates, hence may incur in more uncertainty in the results.

To first grasp the behavior of wealth-income ratios I plot in Figure 2.4 the time series for the four countries. We can recognize two different behavior, one for European countries, the other for U.S. In Europe wealth ratios have followed

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2.5. EXPLAINING WEALTH RATIOS IN 1870-2010 23 a U-shaped pattern: starting with high level at the end of the 19th century, then

decreasing during the world wars, then rising again in the second half of the 20th

century up to the previous levels. Moreover, actual growth and saving rates suggest that the ratio may exceed previous levels, reaching unprecedented extents. In U.S. the behavior of the wealth ratio differs from the European one in the first half of the series, where its levels where lower than the others. By consequence the fall in the ratio after 1929 and the world wars has been less dramatic and less intense, since war affected European territories for the most part. So at the end of the wars the U.S. had the highest ratio in the sample. From this starting point, in the second part of the series, the behavior of the ratio has followed the one of the other countries, with an increase in the ratio towards its previous levels, only halted by the 2009 crisis. ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 400 500 600 700 Years Pr iv ate W

ealth − National Income Ratio (%)

1870 1890 1910 1930 1950 1970 1990 2010 ● ● USA Germany France UK ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Figure 2.4: Private Wealth - National Income Ratios for the years 1870-2010

To add some particulars to the picture I’ve plotted the ratio of public wealth and net foreign wealth with national income in Figure 2.5. We can see that public wealth has had an inverted-U pattern in the period after world wars, but with a magnitude not enough significant to affect the patterns of national wealth ratio: private wealth has always been of different orders of magnitude higher than public

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24 CHAPTER 2. WEALTH ACCOUNTING wealth. Moreover net foreign wealth has had a huge decrease in the 20th, with a

recovery only in the years before 1990.

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● −150 −100 −50 0 50 100 Years Pub lic W

ealth − National Income Ratio (%)

1870 1890 1910 1930 1950 1970 1990 2010 ● ● USA Germany France UK ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 50 100 150 Years F oreign W

ealth − National Income Ratio (%)

1870 1890 1910 1930 1950 1970 1990 2010 ● ● USA Germany France UK ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Figure 2.5: Government/Foreign Wealth - National Income Ratios for the years 1870-2010

Moving on the decomposition of wealth ratios it’s immediate to observe, by calculating average rates for the whole period, how in the long run capital gains have little explaining power. They account for a little positive share for every country except for Germany, which has a negative share. Hence the steady state law β = sg seems to be a satisfying explanation for the very long run. It Table 2.5 I report the long run decomposition.

Moreover we can observe the evolution in the long run of capital gains, calculat-ing the average growth rate for every country in each of the subperiods. By plottcalculat-ing them we can see how the asset price recovery hypothesis, that I’ve formulated before, might be verified. France and U.K indeed exhibit a U-shaped curve for capital gains, while Germany seems to not have yet recovered from the asset price drop in the afterwar.

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2.5. EXPLAINING WEALTH RATIOS IN 1870-2010 25 ● ● ● ● −2 −1 0 1 2 Subperiods

Capital Gains − National Income Ratio (%)

1870−1910 1910−1950 1950−1980 1980−2010 ● ● U.S. U.K. Germany France ● ● ● ●

Figure 2.6: Evolution of Capital Gain- National Income Ratios for the years 1870-2010

To conclude with the last piece of evidence, I show the effect of the two wars in the last table of the chapter. The decrease in national wealth-national income ratios in the period 1910-1950 can be decomposed in its determinants: the effect of the initial level of wealth, the decrease in wealth due to war destructions, the decrease due to variation in savings and finally capital gains or losses.

Interestingly, the major cause of decrease in wealth has not been the physical destruction but either the insufficient level of savings accumulated in the period

gw gws q gwsgws+q gwsq+q

USA 3,4 2,6 0,8 76% 24% U.K. 1,8 1,5 0,3 83% 17% Germany 2,0 2,6 -0,6 128% -28% France 2,0 1,8 0,2 91% 9%

Table 2.5: Decomposition of real growth rate of national wealth(gw) in its savings and

capital gain components (gws and q) with relative shares. Periods 1870 and 2010, the

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26 CHAPTER 2. WEALTH ACCOUNTING or the capital gains and losses. For the first thing, it may be the consequence of human losses and destruction of means of production: in a country made poor by the war, people owned nearly nothing and earned little, hence weren’t saving enough to maintain the same wealth ratio. For the second effect we must remember the decrease in asset prices and also add foreign wealth variations, which have been negative due to the collapse of colonial empires.

β1910 β1950 initial wealth savings destruction q

Germany 637% 223% 400% 109% -120% -165% (31%) (29%) (40%) France 747% 261% 421% 144% -132% -172% (38%) (27%) (35%) U.K. 719% 208% 409% 75% -19% -256% (46%) (4%) (50%)

Table 2.6: Decomposition of the variation in βnt during World Wars in the effect of initial

wealth, savings, destruction and capital gains. In parenthesis the relative shares.

2.6

Final Remarks

As we have seen throughout the chapter, the accounting equation for β, in both its steady state and short run version, seems to fit pretty well with the data available. Both wealth decomposition of the period 1970-2010 and 1870-2010 have shown a consistent picture, from which I have drawn likely explanations of the movements in wealth ratios, both by looking at data and at historical events. One more time, I should remind that the analysis is not without flaws. Both errors in measurement and lack of data, may be the cause of some change in the picture we have observed, affecting some of the conclusions I have derived, especially for pre-war periods. Nevertheless, even with some imperfection, the dataset represent a solid base for wealth accounting in the last century.

The weakness of the dataset then relies more in its limited extent: only 8 series are available1, of these only 4 reach years before 1970 and this represent a real

1I excluded Canada e Australia from the presentation in order to have a more clear view of

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2.6. FINAL REMARKS 27 obstacle for testing effectively the explanatory power of the theories I’ve exposed. Starting from this lack of data, I’ve tried to fill the gap for the Italian series, estimating a data point for pre-war Italian wealth. The methods and the results I’ve obtained will be shown in the next chapters, first by looking at estimates made via bequests by other scholars (Chapter 3), then by framing this estimation in a theoretical model of savings (Chapter 4) and finally by trying to obtain an estimates for the year 1927 (Chapter 5).

By looking at the bequested share of wealth, we are allowed to introduce also the distributive aspect of the wealth accounting issue. Indeed, since now, looking at wealth ratios only didn’t showed the emergence of a clear theory of distribution of wealth. Instead, by checking the share of wealth bequested and trying to explain its magnitude push toward the formulation of clear distributive claims and policy implications. Again the work of Piketty will be the guide on this issue too, with his work on French bequested wealth: “On the Long Run Evolution of Iheritance”.

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Chapter 3

Historical Estimates of Wealth

3.1

Accounts of Italian Wealth:1966-2011

In the previous chapter the time series of Italian wealth weren’t available for years before 1970. As a matter of fact also the years from 1966 to 1970 are present in the accounts, but I haven’t show them to maintain consistency among countries. This data have been provided by different sources, according to the type of wealth they referred to. For private wealth, we distinguish among financial and non-financial assets: the Bank of Italy provided accounts of financial assets for the whole period, while for non-financial assets of households it only covered the years 1996-2011 via its Supplements to the Bank of Italy’s Statistical Bulletin. Non-financial assets for the period 1966-1995 have instead been provided by the work of Brandolini et al (2007).

For government wealth the situation is different: while for financial assets we can still rely on the Bank of Italy accounts, there are no time series of non-financial assets available for the whole period. The device used to bypass this difficulty is to use an estimate made by Istat for the years 2006-2008 and apply the government wealth-national income ratio obtained, 52%, to the whole period. Obviously this approach is far from optimal but there are reasons that make it a tolerable choice. First it’s consistent with the Italian pattern of public investment, which has been constant in the whole. This is reinforced by the fact that there haven’t been particular policies of privatization during the period, which would have caused

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30 CHAPTER 3. HISTORICAL ESTIMATES OF WEALTH imprecisions in the estimates. Moreover the pattern is similar to the one of other European countries, which exhibit constant investments in the same period. Finally, non-financial wealth compared to the enormous public debt accumulated by the Italian government, can be considered less relevant for the whole picture.

A few adjustment were necessary to make these accounts compliant with the NSA regulation, but beside these issues, the thing that appear more evident is the absence in the dataset of data before year 1966. In order to achieve a major scope in the analysis I will now introduce a second type of data, which has been obtained via estimates and hence not used in the previous analysis. The motivation is to separate data which comes from different methodology, in particular since now census method estimates were preferred to perpetual inventory ones and, when possible, direct measurement were preferred over estimation. By reporting this new accounts I hope to give a general idea of wealth before 1966, in order to see if roughly coincides with what official accounts have shown for the other countries. Moreover I will introduce the methods used to obtains a new estimate for year 1927.

3.2

Historical Estimates

3.2.1

The Earlier Estimates

The matter of estimation of wealth was a common topic for economist in the 18th century. Both the academic and the political authorities agreed that the total

wealth would represent a meaningful measure of the richness of a nation and hence in every industrialized states an effort was made to calculate the magnitude and the nature of wealth. The approach used wasn’t different from the one we have seen until now, at least theoretically: wealth was accounted for its market value by surveying the amount of each type of wealth. Actually, being wealth less diversified, financial wealth not enough developed and housing capital still not valuable as today, the task was easyer to pursuit than today. We can list in this “wave” of estimation Foville (1893) and Colson (1903) for France; Colqhoun (1815), Giffen (1889), and Bowley (1920) for the United Kingdom; King (1915) for the United

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3.2. HISTORICAL ESTIMATES 31 Nevertheless, after the 30’s of the 20th century, this line of research ceased to

be pursued with the same interest since the issues of unemployment and growth moved the focus of economist toward the measure of national and personal income. Hence we assist to a sort of break in the estimates, which luckily for some countries was filled by national accounts, but for others has still to be.

The Italian case belongs to the second group of countries. Like other developed countries at the end of the 19thscholars took part to the wealth estimation wave. We

can list Pantaleoni, Benini, Bodio, Sensini and Einaudi in this group. Nevertheless we should highlight the limitations of their work which was due to the lacking of interest in the public debate and by the statistical institutions: they were more a personal initiative of academic and public officials, which then suffered from severe restraint in statistical data. This is highlighted by the debate which followed the first estimates and involved Gini and Princivalle: Gini demonstrated that estimates were done using outdated data and unlikely assumptions. After these critics wealth estimates became more rare, as I’ve said before, and there has not been any official account documentation. The more complete series is the one from Retti-Marsani (1936), which makes annual estimates from 1901 to 1934. This series has then been extended to 1938 by De Vita (1941) and seems to be consistent with the critiques of Gini.

These works are still to be transposed in the actual Italian debate, as I said in the introduction of this thesis. Wealth has not been an argument as central as income and hence there aren’t works which try to joint and evaluate all this sources in a consistent manner. In what follows then, I will report the work of Baffigi (2008) which tries to re-evaluate wealth in the period 1872-1913 by applying the Gini methodology to older estimates and join this new estimates to the other ones available.

3.2.2

Methodology of the Estimates

In the first chapters of its work, “L’Ammontare e la Composizione della Ricchezza” , Gini reviews the various methods applied to estimate wealth in different countries. The variety of statistic data among countries in those years made impossible to label one method as optimal, since each of the methods had the aim to deal with

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32 CHAPTER 3. HISTORICAL ESTIMATES OF WEALTH different difficulties in which the scholars were incurring. Hence starting from the amount and quality of statistical source available for one country a method was chosen.

When a lot of sources were available, the more precise way to estimate wealth was the inventory method . It was the ideal precursor of the method followed in the national accounts, hence the one seen more reliable by Piketty and also by economist of the time. It consisted in a survey of wealth divided by categories, using for each category a different set of sources and assumptions and has been used in the United States, thanks to a ten-year census of wealth starting from 1840.

When instead of direct surveys of wealth, only source of income were available, the income capitalization method was used. It consisted in establishing different categories of private capital according to the sector or profession in which that capital was invested , then measuring the income of those sectors and determining a reasonable discount rate. By multiplying income of sectors by a capitalization coefficient derived by the discount rate, the total wealth of those sector was found and hence private wealth of the country was obtained by the sum of those products. This method had been applied by Robert Giffen in 1878, to estimate wealth in the U.K via income tax data.

Finally when the statistical material was very poor and other sources weren’t available, the method use was the inheritance tax method. This method was pioneered by De Foville for the French data in 1878 and was deemed as the worse by the economist which first used it for Italy. Indeed, Pantaleoni in 1890 used this method to make the first estimation of wealth, justifying himself by pointing at extreme poverty of statistical data in Italy. Thus, this methodology would be applied in the next years by many other scholars which tried to calculate Italian wealth.

The De Foville method consisted in using inheritance tax data to calculate total wealth of a country. If the inheritance tax rate for a certain year was τt and the

total amount of inheritance taxes was TtI, then total bequested wealth was equal to Bt = TtI ·

1

τt. Now, to estimate total wealth, scholars followed this reasoning:

bequested wealth represents the share of wealth which passes with death , hence it’s a fraction of total wealth equal to the ratio of the number of death owners with respect to the total of the population. Since this ratio it’s the definition of

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3.2. HISTORICAL ESTIMATES 33 mortality rate, then, by multiplying bequested wealth by the inverse of this rate, total wealth would be obtained. Assuming moreover that, due to different causes, a certain share of wealth was not declared, the wealth multiplier should be corrected by a coefficient of evasion.The theoretical equation linking total bequests with total assets would then be:

Bt= 1 1 + et · mt· Wt= λWt ⇒ Wt = 1 λBt

Where λ is the wealth multiplier, mt represents mortality and et the correction for

unreported wealth.

3.2.3

The Debate on Multipliers

The above formulation in its simplicity hides most of difficulties in estimation which scholars were dealing with. In fact it is based on a lot of oversimplifications which can be divided mainly in two type: distribution of wealth assumptions and demografic simplifications.

For the first issue one can see that, by multiplying bequested wealth with the inverse of mortality, an implicit assumption was that wealth of individual passing away was distributed as the wealth of people living. It might be instead that dying people had relatively more wealth in their hands than surviving population or vice versa. Hence the formula should be updated with a correction µ for the share of bequested wealth with respect to total wealth:

Bt= 1 1 + et · µ · mt· Wt = λ∗Wt⇒ Wt= 1 λ∗Bt

The obvious reason for making the assumption of uniform distribution is that µ cannot be estimated without knowing the level of wealth, which is the unknown of the process; nevertheless it’s a simplification that must be reminded. Moreover another effect of wealth which was ignored is the correlation among wealth and mortality: in a developing country as Italy at the early years of 1900, having more wealth would certainly means to have better chance to survive, hence to be under-represented in the bequested wealth. Again, statistical methods and sources weren’t enough detailed to avoid this effect, and hence mortality was assumed

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34 CHAPTER 3. HISTORICAL ESTIMATES OF WEALTH independent from wealth.

The demographic simplifications were instead more easily recognizable, even for the scholars of that time. Indeed the first estimates used the so-callled mortality multiplier method, which assumed a static demography, with life expectancy and mortality constant. This was in striking contrast with the reality of industrial countries which were in a phase of demographic transition. To overcome this bias the method applied by De Foville used the so called devolutionary interval: the average number of years elapsing between the time a generation gets its inheritance and the time it dies. De Foville calculated this interval at 36 years and claimed it to be constant. The reality was instead , as demonstrated in 1907 by Coletti, that even this interval was changing over time, hence the assumption of invariance was wrong.

A full review of all the methods of wealth estimation is made by Gini in its work, where he highlights the shortcomings of each one making observations on multipliers similar to the previous ones I’ve made. He then proceeds to propose another method, which tries to combine the advantages of each of the previous ones. The method is called by Gini the “multipliers” method and proceeds as follows: first some categories of wealth must be estimated by inventory or capitalization method, hence avoiding unreal assumptions on demography and wealth distribution; then, once the value of each category is known, this value must be divided by the relative value of bequested wealth. With these procedures one should obtains a certain number of multipliers, one for each category, that tells the relation among total amount and bequested amount of a certain assets. After this, one should try to estimate multipliers for the other categories in which inherited wealth is divided, which though one cannot measure by income or capitalization method. To do this one should adapt the previous multipliers taking into account differential mortality and rate of evasion for categories of wealth. The final result should rely less on bequested data only and hence be more close to reality.

To make an example: being impossibile to estimates one category of wealth, say valuables, by other methods, to infer the amount of their multipliers one should use the multiplier of another category, say land or houses. Taking into account that evasion is easier with unregistered goods and that valuables are owned by richer,

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3.2. HISTORICAL ESTIMATES 35 and hence healtier, people, then one should make a consequential adjustment to the multiplier and estimates total wealth in valuables with it.

While proposing this new method, Gini was trying to avoid the underestimation caused by the devolutive interval, which assumed constancy of demography and a common behavior of all the wealth categories. At the same time he still proposed his method as appliable intertemporally, hence from year to year, without further adjustments. As Benini demonstrated in 1909, this wasn’t possible, since mortality was varying through years too and not only across variables and this was reflected by changes in the multipliers. Hence a further modfication needed to apply Gini method would be to take into account mortality evolution.

By calling for adjustments also for evasion, Gini made clear another aspect which undermined early estimates of wealth , beside simplifying assumptions. Actu-ally all the estimates of wealth made by first scholars assumed an evasion coefficient equal to 25% on the basis of the the one estimated by De Foville in its work on France. Gini criticized the behavior of its contemporaries to focus on only on the devolutive interval, while using the De Foville’s evasion coeffcient without further adjustment or inquiry, and estimated evasion coefficients by category obtaining an average rate of 46% (Gini 1909). This finding were further supported by another study of Mortara (1909) which observed how the changes in tax rates in Italy in years from 1874-1902 should have increased evasion, he didn’t measured how much, though. Finally, in its 1914 work, Gini published the most extensive treatment of inheritance tax evasion which we can found for the pre-war years. In the 4th chapter

of his book Gini demonstrated the necessity to measure carefully evasion, proving with a large set of empirical examples that changes in declared commodities were having anormal patterns which only evasion might explains. Moreover he analized the structure of tax collection, highlighting its flaws in creating incentives for tax collectors to assess correctly the amount of declared wealth.

The last contribution made by Gini to the debate on wealth estimation regarded the valuation of real estate. In fact in the first years of 1900 wealth estimates for Italy were criticized by many commenters for being too low. While some pointed toward the unreliability of inheritance tax data, Gini claimed that the real

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36 CHAPTER 3. HISTORICAL ESTIMATES OF WEALTH motivation was that inheritance tax evasion was under estimated and this was not only because of the acritical appliance of the De Foville’s coefficient, as we said, but also due to the imprecise work of tax authorities in assessing the real value of real estates. The person which Gini was pointing the finger at was Luigi Princivalle, a functionary in the Finance Ministry, which in its monograph had estimated the value evaded at 12.5% only, deeming the official data on real estates reliable. Gini demonstrated that the method used by the authorities to asses the value of land were inappropriate, since they merely applied certain coefficients to the cadastral assessments. To prove his point he organized an alternative survey in which he asked to the directors of the agricultural improvement service 1 to estimate the

value of land in their province and, if necessary, change the value estimated by the Department of State Property and Taxes. Most of the 27 province surveyed found the values of the Department too lows, hence proving Gini’s point.

Gini then proceeded to make his own estimates for the Italian wealth for the years he had data about. I report in the following table the categories of wealth with their stock values, their bequested amounts and their multipliers for years 1903 and 1908.

1The itinerant teachers of agriculture(“Cattedre ambulanti dell’agricoltura”) have been for

nearly a century, the most important institution of agricultural education, especially aimed at small farmers, with the support of the instances of the most advanced intellectual circles and the world of teaching coming from schools and technical institutes.

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3.2. HISTORICAL ESTIMATES 37

1903 1908

W B µ e W B µ e

(mil.) (mil.) (mil.) (mil.)

Land, rural buildings and livestock

40500 506,440 80 0,21

Urban buildings 16000 262,700 61 0,21

Public debt securities Bearer 3094 17,852 173 3 5500 63,288 87

Reg. 1994 44,590 44 Bonds, certificates, shares, etc. Bearer 2927 21,017 139 3,5 6251 51,157 122 Reg. 846 27,458 30 Savings/security deposits and current accounts

Bearer 1141 5,552 204 1,2 4359 28,290 154

Reg. 2124 24,446 94

Cash deposits with CDP 153 1,789 86 156 1,902 82

Cash 1322 10,725 123 1679 11,434 147

Credits secured by liens 2300 90,040 25

Debts secured by liens 3000 73,000 41

Table 3.1: Total amount of wealth (W ), total bequested wealth(B), ratio of total wealth with respect to bequested wealth (µ) and evasion coefficient (e) for different categories of wealth in the years 1903 and 1908

As we can see there are many data missing: land and urban buildings are estimated only for 1908, while decomposition of titles in registered and bearer type is available only for 1903. Further, evasion coefficients on titles are estimated only on bearer ones, since Gini assumed that evasion was more difficult with registered ones and hence irrelevant.

Nevertheless Gini was able to estimate wealth for Italy in 1908. He firstly added to the sum of the value I showed, which is around 74,5 billions, 3 billions of furniture wealth and 5 billions of other types of mobile goods which he derived by applying to the bequested amounts of those goods the same multiplier of urban buildings. Interestingly this measures were consistent with those of Princivalle and were similar to those of other countries, hence likely. Finally, taking into considerations all others type of wealth which have not a measured amount but are present in the country, he concluded that the total amount of Italian wealth was

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38 CHAPTER 3. HISTORICAL ESTIMATES OF WEALTH no less than 80 billions of lire, a measure higher than all the others available at the time. Princivalle indeed estimated for the same year 61,65 billions while Coletti for the years 1900-1905 47,5 billions; Nitti finally, for year 1904, had revised his inital estimate of 50 billions up to 65.

3.2.4

Italian Wealth Estimates after 1908

Before moving to the time series obtained by Baffigi I would like to revise the chapter 3bis of Gini’s book. In this chapter, added in the second edition of the book and curated by Paolo Quirino, there’s a full review of all the estimates of Italian wealth made by different authors in the years after 1908. There isn’t a complete discussion of the whole methodology and assumptions in each of the estimates but the author distinguishes between the estimation methodology and I think that this can be a useful reference for building a complete time series from the end of 1800 to 2011. I’m reporting in the next tables the estimates as divided in the chapter in three periods: 1908-1917, 1918-1939, 1940-1956.

Three facts are worth nothing. First the enourmous increase of the value of nominal wealth in the whole period: from 1908 to 1956 wealth should have increased 600 times according this figures. Obviously the measures must be rescaled, taking into account the devaluation of currency in the war period. I’ve done this by rescaling the values reported in Chapter 3bis to the value of currency in 1872, being this the lower limit of the series of Baffigi which I will show later. Second, the evaluation methods: after the work of Gini, other scholars seems to have understood the pitfalls of the devolutive interval method and have moved toward the inventory and capitalization method. Third, the number of estimates: after Second World War we see a decrease in the number of estimates, which the author ascribes to the effect of war destruction and destabilization of the economy.

In this brief review, I unfortunately cannot show more details on the methodology followed by each author, moreover the single estimates are not consistent with the other due to changes in assumption, methods and set of data. Hence I would be a useful reference for the next series I’ll show, to see if there’s a certain consistence amonge estimates and if some method seems to over estimate or under estimate the amount of wealth.

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3.3. ITALIAN WEALTH SERIES 39

Year Author Type Method £ current £ 1872

1908 Gini Private Inventory 80-85 81-86

1910 Santoro National Capitalization 74,5 76

1910-1911 Colajanni Private Devolutive Interval 80 79

1911-1912 Finance Ministry Immobiliar Devolutive Interval 49,8 49

1912 Gabrielli-Wiseman Private Capitalization 93 91

1912 Benedetti Private unknown 90 88

1912 Flora National Inventory 92 90

1912-1913 Tivaroni Private Devolutive Interval 74 73

1913 Coppini Private Inventory 90 88

1913-1914 Colajanni Private Devolutive Interval 100 98

1913-1914 Tivaroni Private Devolutive Interval 74,9 73

1914 Gini Private Inventory 111 109

1914 Dettori Private Devolutive Interval 95 93

1914 Corniani Private Inventory 100 98

1914 Tivaroni Private Inventory 100 98

1916 Griziotti Private unknown 65-70 48-51

1917 Gini Private Inventory 117 61

Table 3.2: Estimates of Italian wealth in the period 1908-1917, with methodology and author. Amounts in billions of lire.

3.3

Italian Wealth Series

In this last section of the chapter I will show two long series of estimation of Italian wealth before those of 1966. I separated them from the single year estimates since they’re continuative series collected by the same author, hence they have, in my opinion, more internal consistency and I think can be compared with each other and commented. Moreover they belong to separate periods, hence they may highlight both view on wealth: the one of those trying to estimate wealth in their time, with limited amount of data, and the one of those who try to estimate wealth in history, looking at previous estimates and trying to achieve better methods.

3.3.1

Retti-Marsani’s series for 1908-1934

The first series has been compiled by Retti-Marsani in 1936, through the real inventhory method hence taking into account Gini’s considerations, completing missing data with the capitalization one. The series spans from 1901 to 1934, but

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40 CHAPTER 3. HISTORICAL ESTIMATES OF WEALTH

Year Author Type Method £ current £ 1872

1921 Pellegrini Private unknown 353 83

1924 Tivaroni Private Inventory 500 115

1924-1925 Gini Private Inventory 550 113

1926-1927 Sacerdote Private Inventory 547 114

1928 Mortara Private unknown 450 101

1928 Degli Espinosa Private Inventory 475 106

1928 De Vita Private Inventory 510 114

1928 Lasorsa Private Inventory 455 102

1928-1929 Tivaroni Private Inventory 470 104

1931 Tivaroni Private Inventory 400 101

1932 Virgilii National unknown 333 86

1935 De Vita Private capitalization 426,3 122

1936 De Vita Private capitalization 430,7 115

1936 Degli Espinosa Private capitalization 538,6 143

1937 De Vita Private capitalization 546,4 133

1937 Degli Espinosa Private capitalization 620,7 151

1937 Thaon di Revel Immobiliar Inventory 297 72

1938 De Vita Private capitalization 566,7 128

1938 Vinci National capitalization 748 169

Table 3.3: Estimates of Italian wealth in the period 1921-1938, with methodology and author. Amounts in billions of lire.

Year Author Type Method Amount Corrected 1872

1951 Livi National capitalization 37000 157

1956 Barberi National capitalization 49080 177

1956 INEA Land capital capitalization 11000 40

1956 INEA Agricultural capital capitalization 3690 13

Table 3.4: Estimates of Italian wealth in the period 1951-1956, with methodology and author. Amounts in billions of lire.

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