Silviase/jgov_v1.4_full_ann huggingface dataset:
cally uncorrelated each relation can be estimated separately, while if relations are stochastically dependent they should be estimated jointly. (Cf. the old discussion of recursive and interdependent models.)

A particular feature of SESIM is that each individual each year is assigned a “status”. There are nine different statuses, and with the exception of the status emigrated an individual can have one and only one status in a year. The nine statuses are:

1 child (0-15 years old)

2 old age retired; individuals with income from old age pension

3 student; individuals who study at gymnasium, adult education or university

4 disabled; individuals who have disability/sickness benefits

5 parental leave; women who give birth during the year

6 unemployed; individuals with income from unemployment insurance or from labor market training

7 miscellaneous

8 employed; individuals in market work

9 emigrated; individuals living abroad with Swedish pensions rights. (Note, this classification is not unique because emigrated can have income from early or old age pensions.)

Status determines income: For employed (status 8) earnings are determined by an earnings function, unemployed (status 6) get unemployment compensation according to the rules for this kind of benefits, disabled (status 4) get disability pension, etc. The assumption that one can only have one status in a year is of course not fully realistic. In real life one can for instance, both study and have a job in the same year, and it is also possible to be retired in the sense of drawing a pension and at the same time do market work. In our study of population aging (cf section 3.5 below) the mechanisms through which people leave the labor market was important, and not being able to allow for part-time work and part-time retirement was an unfortunate constraint. However, the decision about the status concept was taken early on in the construction of SESIM and it is a key concept in determining the direction of simulations. To drop the status concept or to give it a different meaning had implied that we had to reprogram the model completely.

SESIM is a stochastic simulation model, which means that all events that involve a behavioral model are the result of a stochastic experiment, a draw of random numbers. The outcome of one simulation round will therefore in general differ from the outcome of another one, even if the starting point was the same. This is not only the result of drawing different random numbers but also of the model choosing different paths as a result of different outcomes of the
random experiments. For instance, in one simulation an individual might have been simulated to participate in market work, while in another he might have become unemployed. As unemployed he will get lower income, which will have implications for other choices.

One way to reduce the random variation created by the stochastic properties of the model is to increase the sample size, another to use methods that are based on replicated simulations such as the bootstrap method, and a third approach is to align the model to known totals or means, i.e., the model is forced to replicate these totals and means. $ ^{4} $ In SESIM alignment is usually used in the demographic module to make simulated population totals such as the age-specific number of births, number of deaths, and number of migrants coincide with the demographic statistics and forecasts from Statistics Sweden. It is also used to make the total number of unemployed agree with official statistics and the medium term forecasts of the Ministry of Finance.

Another reason to align to official forecasts like the demographic forecasts of Statistics Sweden is to make the outcome of the simulations comparable to other studies. One avoids in this way that differences in demographic scenarios explain differences in other target variables, such as for instance the number of elderly that utilize social care.

Alignment can, however, be misused. If the model systematically simulates totals which differ significantly from known totals, it suggests that the model is misspecified or that the parameter estimates are erroneous. The correct action is then to re-specify and re-estimate the model, not to force it on track by alignment. Even if alignment will make the model replicate the known totals there is no guarantee that the distributions around the means implied by the totals will become correct, and these errors will tend to spread to other modules as the simulation proceed. $ ^{5} $

SESIM is limited to the household sector and there is no macroeconomic feedback built into the model. Instead it is possible to feed certain macro indicators exogenously into the model. They are: the annual rate of inflation, the rate of return to bonds, stocks and shares, the annual average rate of change in wage rates, and the unemployment rate. It is thus possible to simulate under alternative growth and business cycle scenarios, but there are no market price changes resulting from the actions of households.

### 3. Policy applications of SESIM

### 3.1 Public support to students

#### 3.1.1 Policy issues

Higher education in Sweden is free of admission charges and the government also provides loans and cash benefits to students. The sum of loans and benefits should in principle cover
degree and those without is higher for women than for men. Women also live longer and thus enjoy the pension benefits for a longer period.

Table 3.1 Life-cycle incomes and return to higher education

Non university program	Short university program	Long university program
Males	Females	Males	Females	Males	Females
Life-cycle income (1000 SEK)	6974	5120	7727	5911	8861	6752
Total return to education (1000 SEK)	0	0	753	790	887	631
Rate of return to education per year %	6.0	8.7	4.9	6.3
Source: Table 5.2, Ericson and Hussénius (2000)

Table 3.2 Share of students with loans who get their loans remitted at the age of 65 by gender and length of schooling.

Interest rate (%)
0	1.3	2.8

Males	7.6	21.7	38.2
Females	26.1	41.4	53.2
Less than university	5.0	7.4	13.2
Short university	4.4	11.1	17.7
Long university	23.3	41.8	58.8
Source: Tables 5.7 and 5.8 in Ericson and Hussénius (2000)

Table 3.2 displays how the share of students with loans who get their loans remitted at the age of 65 depends on interest rate, gender and length of schooling. The results are quite sensitive to the assumption about interest rates. Females have much higher remittance rates than men. The explanation is that they work less in the market and get lower incomes. The rate also increases with the duration of the studies because the loans then increase in size and the time span with market work becomes shorter.

Even with moderately high interest rates these shares are pretty high and the total amount remitted is of about the same size as the total of all cash benefits. The government decided al
ready in 2001 to make the rules governing repayments less generous, such that almost all students would have to repay their loans completely before the age of 65.

### 3.2 Lifetime Redistribution through taxes, transfers and non-cash benefits

#### 3.2.1 Policy issues

Which are the redistributive effects of taxes, transfers and non-cash benefits? To what extent do these effects depend on the length of the perspective – a year or a life-cycle?

To what extent does the redistribution performed by the public sector reallocate resources between individuals, and to what extent does it result in an intra personal redistribution, for instance from working life to old age?

These issues were studied using the capability of SESIM to simulate whole life-cycles. The results can be found in SOU 2003:110 and in Pettersson and Pettersson (2007). The authors claim that a life-cycle perspective is indispensable when designing new taxes and benefits. If it is forgotten in favor of only a short term perspective, one will not see that the long-run effects of a new policy might not become those intended.

#### 3.2.2 Simulation results

Total income was defined as disposable income less indirect tax paid divided by an equivalence scale, plus non-cash benefits without equivalence scale adjustment. Life-cycle income was then defined as the mean of all total incomes over the life-cycle.

Table 3.2.1 Gini coefficients by income concepts

Annual income	Life-cycle income
Market income	0.490	0.196
Equivalent disposable income	0.217	0.102
- Indirect taxes	0.224	0.104
+ Non-cash benefits	0.189	0.086
Source: Table 1, Pettersson and Pettersson (2007)

Table 3.2.1 displays how the Gini coefficient depends on income concept. Life-cycle incomes are more equally distributed than annual incomes, and total income is more equally distributed than disposable income, which in turn has a Gini coefficient that is about half of that of market incomes. Taxes and benefits thus have a major equalizing impact on the income distribution.

The authors also decompose the Gini coefficient into a weighted sum of concentration indices to investigate how the various income sources contribute to the total Gini. They find that most
income sources, such as social security, transfers to family and children, student benefits and income taxes are progressive both annually and in the life-cycle. Market income, occupational pensions, expenditures for old-age care and indirect taxes are regressive.

The only major income source which shifts from progressive to regressive when one goes from annual incomes to life-cycle incomes is old-age pension. In a cross-section of annual incomes old-age pensioners usually have lower incomes than average, but in a life-cycle perspective high pensions are based on high incomes, and high income earners also tend to live longer than average.

Even if almost all income sources have the same type of impact on the Gini coefficient for annual as well as life-cycle incomes, the relative contribution to the Gini depends on time horizon. For instance, the regressive effect of market incomes is less on life-cycle incomes than on annual incomes, while the regressive effects of disability pensions and income taxes are higher on life-cycle incomes than on annual incomes.

This study also analyzed who is gaining and who is losing over the life-cycle by the public sector. Those who get more transfers and non-cash benefits than taxes paid will have a net gain. In this part of their study the authors did not only include direct taxes but also indirect taxes and social security contributions to the extent that the sum of all taxes paid equaled all benefits received for each cohort. They thus assumed each cohort to be financially balanced over the life-cycle. Furthermore, all economic resources of a household was divided equally among all household members, i e no equivalence scale was used. Table 3.2.2 summarizes some of the findings.

Table 3.2.2 Gains and losses through the public sector by gender and income quintile (1000 SEK in 2003 price level)

Men	Women	Quintiles of Life-cycle income	All
Q1	Q2	Q3	Q4	Q5
Taxes	7136	6389	4264	5741	6597	7691	9483	6758
Transfers	3562	4085	3924	3983	3915	3770	3543	3827
Non-cash benefits	2611	3245	2840	3109	3109	2922	2679	2932
Net effect	-963	941	2500	1351	428	-999	-3262	0
Source: Tables 4 and 5, Pettersson and Pettersson (2007)

There is redistribution from men to women. Women have lower incomes and thus pay less in taxes. They receive more benefits such as maternity and family benefits, and at least partly because they live longer they get more health care and social care.

There is also a clear redistribution from high to low income households. The latter pay much less in tax and receive more in transfer payments, while non-cash benefits are more evenly distributed.
There are clear age profiles in the payments between the households and the public sector. Taxes are predominantly paid in working age while benefits are received in the beginning and in the end of the life cycle. Child and family benefits and education come early while old-age pension and health and social care come at the end of life. The balance of payments from and to the public sector starts to become positive at the age of 55, but the cumulative net payments do not become positive until the age of 87. There is thus redistribution from individuals with a short life to those who live long.

Finally, the authors also investigated to what extent redistribution through the public sector resulted in transfers of resources between individuals. They found that only about 18 per cent of the total redistributed was truly a reallocation between individuals, while 45 per cent was annual intrapersonal reallocation (benefits in a year were self-financed through own taxes in the same year) and 38 per cent life-cycle intrapersonal reallocation (old-age benefits were self-financed by taxes paid earlier in the life-cycle).

### 3.3 Intergenerational redistribution

#### 3.3.1 Policy issues

Almost 50 per cent of total production in Sweden is redistributed annually through the public sector. This is done by taxes and fees that are returned to the population in the form of benefits, transfer payments and public consumption. As we have just seen most of the annual redistribution is returned to the same individual – immediately or later in life, for instance as pensions – while a smaller share is redistributed between individuals.

Much of this redistribution builds on an implicit contract between generations. The working population pays taxes and fees to finance child care, schooling, pensions, health care and old age care - services which are primarily consumed by younger and older people - hoping that their children will do the same when they grow into working age. When the size of birth cohorts varies the issue of redistribution between generations arises. For instance, the large post World War II baby boom cohorts had to put up with large school classes and a fierce competition to enter into universities. Their benefits per capita were thus reduced. These cohorts are now retiring and wondering if they will get the generous pensions they have been expecting. In another 10-15 years they will get to the age when they will need much more health care and social care. Will the government be able to continue providing these services? The children of the baby boomers, cohorts which are smaller in size, might ask if they have to pay for the increased provision of public services to their parents by much increased taxes.

To address these issues a study was started within the Ministry of Finance (Pettersson, Pettersson and Westerberg, 2006) with the task to assess the size of any redistribution between now living generations. They also tried to estimate the total life-time consumption potential of a birth cohort, defined as life-time income adjusted by any transfer to or from other generations through the public sector.
#### 3.3.2 Methodology and results

The idea was to compute a life-cycle balance account for each individual of all payments from the individual to the public sector and all payments from the public and services provided by the public sector. These balances were then summed for each birth cohort. An obvious problem is that we do not have observable data covering the whole life-cycle of an individual. The solution was to use the pieces of data that existed and supplement with simulations from the SESIM model. The cohorts studied were born in 1930-2009.

Individual longitudinal register data exist from 1968, but more completely from 1987. Transactions before then were imputed using the latest know distribution and totals from the national accounts as well as various other sources. All transactions after 2004 were simulated by SESIM.

The motivation for this micro(simulation) approach was the following:

1) Even if a cohort had a positive (negative) balance, all cohort members might not have it. There might have been some groups within the cohort which had been in advantage (disadvantage) while others had not. With a microsimulation approach one can analyze the distribution within cohorts.

2) The precision in the simulations of future taxes and transfers becomes much better in a microsimulation approach compared to a more aggregate one, because most tax and benefit systems are non-linear.

3) The microsimulation approach permits the analyst to quite flexibly study the balances for other subgroups than birth cohorts, which makes it easier to understand the outcome and make error corrections.

There are a number of fundamental problems the analysts had to address and the reader is referred to their report for a discussion. Here I will only briefly mention a few. First, all transactions with the public sector, whether they are with the business sector or a foreign agency, are in the end considered to benefit the private consumer. For instance, expenditures for the defense, roads, etc are allocated as benefits across all individuals. Likewise all incomes of the public sector are debited to the household sector.

Second, some kind of discounting is needed to make balances from different years comparable. It is relatively easy to index by a consumer price index $ ^{9} $ , but one might also like to correct for the real growth of the economy. This becomes especially clear when one compares consumption potentials. $ ^{10} $ The authors have chosen to discount with an index of GDP per capita in current prices.

Third, some incomes (and benefits) are individual while others are given to the household. In this study the authors have chosen to assume that there is redistribution within the family such that all family members including children live on the same standard. All incomes are thus
Figure 3.3.1 displays the public sector balances by birth cohort. One might have expected some to be negative and some positive, but they are all positive. The explanation is that the public debt was assumed to be a constant share of GDP, and in combination with economic growth increasing debt makes this result possible. We should thus compare the relative size of these bars. The generations with a relative gain are those born in the 1930s, 1950s and 1980s, while the large baby boom cohorts of the 1940s and 1960s are relative losers. Those born in the 1930s paid relatively low taxes but were able to get the benefits of the increasing welfare state. Those born in the 1980s paid relatively little in tax because they started to work late and were assumed to retire early and use their increased longevity for leisure. The generations of the 1950s paid marginally more in taxes compared to those born in the 1940s but got more both in transfer payments and public consumption. The baby boom cohorts of the 1940s worked a rather long life and thus paid relatively much in tax, while they had to compete for

Figure 3.3.1 Public sector balances for people born in 1930-2009. (SEK, average per year of survival in Sweden adjusted for price changes and real growth.)

SEK per year

Source: Diagram 4.2 in Pettersson & Pettersson (2006)

the benefits from the public sector. The results suggest that the increased pressure on the public sector from the large cohorts has not been met by increased taxes but rather by a reduction in the benefits. The same is true for the children of the baby boom cohorts, those born in the 1960s. The youngest cohorts are also losers in these computations. The explanation is that they pay relatively high taxes but get less of future pension benefits. They were assumed to retire at the age of 65, and if the retirement age does not increase with increasing longevity the current pension system will pay out lower pensions.
Within all generations there are individuals who gain from the public sector and others who lose. In fact, this intra generation redistribution is much larger than the inter generation redistribution.

This study also shows that the average consumption potential by cohort – adjusted for price changes and growth – is completely dominated by the market incomes, while the modest intergenerational transfers through the public sector means relatively little. The results suggest that those who were born in the late 1930s and in the 1940s had a little higher consumption potential than the other generations. The explanation is that these generations came out from the schools into a labor market with a high demand for labor and very little unemployment. They got well paid jobs, were able to save and borrow to buy a home, which then increased in value. Although the baby boomers might have lost in the redistribution game through the public sector they were not losers in a wider perspective.

#### 3.3.3 Conclusions

Most of the taxes an individual pays in a life-time go back to the same individual in the form of transfer payments and public consumption. Only about 20 per cent of the taxes an average individual pays result in redistribution to someone else, and most of this redistribution goes to someone in the same generation rather than to someone in another generation.

This study is limited to redistribution through the public sector and does not include private transfers such as inheritance and inter vivo gifts. Nor does it include indirect behavioral effects of public policy, for instance, increased public expenditures on schooling, which increases the educational standard of the population, might lead to different decisions as to work, incomes and wealth accumulation. The informal sector is not included either. In the older generations it was common among women to work at home. Not including this kind of informal work underestimates the consumption potential for the older generations.

Simulating the future with SESIM and FIMO made it possible to fill in the gaps of missing data. Because both models could be calibrated to the same demographic scenario and used the same macro economic assumptions, it was possible to run the two models in parallel. A closer integration of the two models might have opened for a more realistic distribution of public consumption than equal distribution to everyone.

The results obtained also depend on assumptions about the costs for health care and public care and in particular on the assumption that everyone retires at 65\. The increase in the costs of health care and social care is difficult to predict, because they depend on the introduction of new drugs and new treatments and on the ability of the care organizations to increase productivity. New drugs and new treatments are often expensive, but they might increase productivity.

The assumption that everyone, who retires with old-age pension, does it at the age of 65 is unrealistic. The share of people who retire early is not small. It would have been interesting to allow people to retire both before and after 65 in the simulations. SESIM now includes a