The role of wealth taxes for mobility to tax havens
Rising capital shares of income and associated increases in inequality observed in many developed countries have spurred new interest in the taxation of wealth. Many of the academic and policy discussions have focused on whether wealth taxes are enforceable if taxpayers avoid or evade them. The reason is that taxpayers might respond by hiding assets in tax havens, as there is evidence that a signi cant fraction of nancial assets owned by the wealthy is held o shore (Alstads ter, Johannesen, and Zucman, 2019; Zucman, 2015). In part, this was a motivating factor in Piketty’s 2014 call for a global wealth tax: \if all countries do not implement a wealth tax, then mobile capital would simply ow to tax havens where wealth tax rates are zero ».
Despite the relevance of annual wealth taxes in recent policy debates, evidence on the behavioral responses to wealth taxes is relatively small (Brulhart et al., 2016; Londo~no-Velez and Avila-Mahecha, 2018; Seim, 2017) and on migration, in particular, almost non-existent. Moreover, very little is known about how these behavioral responses might shape regional wealth inequalities between sending and receiving regions. The lack of studies on wealth taxes has been partly driven by limited sources of exogenous variation in wealth taxes, which often times are implemented at the national level. Given the di culty of cross-country comparisons, little variation in wealth taxes exists across individuals or regions within a country. Furthermore, any study of migration must know where the taxpayer originated and migrated to, which requires potential harmonization of multiple countries’ administrative tax records.
The third chapter of this thesis moves a step forward by studying the e ect of annual wealth taxes on migration. We take advantange of the unique decentralization of the Spanish wealth tax system in 2011, after which all regions raised positive tax rates except from Madrid. Our ndings reveal that Madrid’s status as a tax haven has attracted a disproportionally share of wealthy. We show that these migration responses have exacerbated regional wealth inequalities and eroded the e ectiveness of raising tax revenue and curving wealth concentration.
Determinants of the increase in housing prices since the late 1990s
The recent rise in wealth to national income ratios has been mostly related to the increase in housing assets’ prices (Piketty and Zucman, 2014; Rognlie, 2014; Bonnet et al., 2014). This literature corresponds to scholars’ increasing interest in understanding the long-term evolution of housing markets (Davis and Heathcote, 2007; Knoll, Schularick, and Steger, 2017) and in particular, the recent rise in housing prices (Mankiw and Weil, 1989; Favara and Imbs, 2015; Saiz, 2010; Glaeser, Gyourko, and Saks, 2005; Gyourko, Mayer, and Sinai, 2013). Scholars have pointed to various underlying mechanisms, and many explanations seem to apply to the Spanish housing boom of the early 2000s. The rst strand of the literature has focused on the positive impact of population increases on housing prices (Mankiw and Weil, 1989; Combes, Duranton, and Gobillon, 2019). In Spain, the increase in the foreign-born population|from 2% of the working-age population in 2000 to 14% in 2008|seems to be one of the principal causes of the increase in housing prices. Gonzalez and Ortega, 2013 and Sanch s-Guarner, 2017 quantify this e ect and show that between one-third and one-half of the increase in housing prices during the 2000s is explained by foreigners arriving in Spain. A second set of studies have related changes in the credit market|through loose monetary conditions and soft lending standards|to the housing boom. For example, Jorda, Schularick, and Taylor, 2015 show the causal relationship between loose monetary conditions and the rise in housing prices due to the expansion of mortgage credit. The authors argue that Spain during the 2000s is a fruitful subject for a case study to analyse, given the signi cant di erence between the Taylor rule’s policy rate and the actual interest rate set by the ECB. Jimenez et al., 2014 and Akin et al., 2014 also present evidence of too relaxed lending standards and excessive risk-taking by nancial institutions during the recent Spanish housing boom.
Other scholars have emphasized the importance of foreign capital ows and hous-ing booms (Sa, Towbin, and Wieladek, 2014), especially with regard to the USA (Bernanke, 2005; Himmelberg, Mayer, and Sinai, 2005; Favilukis et al., 2012; Ferrero, 2015). However, research examining European countries has been more limited, with most analyses focusing on the Eurozone’s current account imbalances (Belke and Dreger, 2013), and the relationship between debt in ows and domestic credit growth (Hale and Obstfeld, 2016; Lane and McQuade, 2014). The literature on Europe has hardly considered the impact on housing prices. In Spain, Fernandez-Villaverde, Garicano, and Santos, 2013 and Jimeno and Santos, 2014 have already highlighted the importance of foreign capital in ows to understanding the recent credit and real estate boom. Nonetheless, these studies only brie y document the importance of capital ows, and neither perform a detailed analysis of the channel nor quantify its importance. In Section V, we build upon the research of this last group of scholars and conduct a descriptive and quantitative analysis that relates foreign capital ows with the growth in household credit and the evolution of the real estate market.
Concepts, methodology, and empirical esti- mate
In this study, we use the concepts of national income and wealth from the international system of national accounts (SNA 2008, ESA 2010). Wealth is calculated by providing, for a particular point in time, a balance sheet that records the economic value of assets owned and liabilities owed by an institutional unit or group of units at prevailing market prices. At the country level, national wealth can be de ned by two related but di erent measures. The rst follows what Piketty and Zucman, 2014 call the market value of wealth, which is the sum of personal and government net wealth. In this de nition, corporate capital is captured mostly by the market value of equity holdings owned by households and the government. This approach di ers from SNA standards, which are referred to by Piketty and Zucman as the book value of wealth, i.e., the sum of non nancial assets of all resident sectors and the net foreign wealth.
We reconstruct national wealth comprehensively by adopting these di erent per-spectives1. First, we compute national wealth at market value during 1900-2017 by calculating the household and government net worth positions. For both sectors, we estimate nancial wealth| nancial claims net of liabilities|to which we add non – nancial assets. Households’ non nancial assets are decomposed into three categories: housing (that includes the value of both the structure and the underlying land), agricultural land, and unincorporated business assets other than agricultural land. Similarly, for the government sector, we decompose non nancial assets into produced assets (buildings and constructions, machinery and equipment), land underlying public buildings, and forest land owned by local authorities.
In this procedure, we follow the SNA recommendation that uses the census-like method as the best valuation technique. Values of agricultural land and housing, which clearly constitute the two most important asset components in the long run, are estimated by multiplying the observed quantities (land areas or housing stock) by representative unit prices. For each period, we gathered the most re ned data on prices to consider variations due to regional di erences and diversity of uses (e.g., di erentiating by crop types in agriculture, or between price-regulated and non-regulated houses). Both wealth aggregates include the value of the underlying land and produced assets (cultivated crops and dwellings, respectively). For housing, we combine and adjust various available sources (Bank of Spain, IVIE, and the Ministry of Public Works) of data on housing prices to produce a more accurate estimate. We perform thorough robustness checks for our housing wealth series, considering all other possible sources and methods. In particular, we compare our series to available estimates by Naredo, Carpintero, and Marcos, 2008, Perez and Uriel, 2012, Bank of In this section, we brie y summarize our approach. The appendix provides a thorough and more detailed discussion of the sources, concepts and methodology used to reconstruct our wealth series between 1900 and 2017. We also include therein several robustness checks we have performed to prove the reliability of our series.
Spain and J. Carmona, Lampe, and J. Roses, 2014. We also consider Spain from an international perspective, using the house price series in Jorda, Knoll, et al., 2019 and the housing wealth series from household wealth surveys. Overall, regardless of which source or method we use, the trends and levels in housing wealth are broadly similar.
Values of nonfarm unincorporated business assets owned by the household sector are estimated by taking as a starting point the results of the Survey of Household Finances available for 2002-2014 and subsequently upgrading the declared values to account for undervaluation and top-coding. We extend the results until the early 1980s by assuming the evolution to be similar to that of assets of non nancial corporations. For the public sector, we use the series of Mas Ivars, Perez Garc a, et al., 2015 for government-produced assets and add the value of the underlying land and forests.
Aggregate Wealth: Concept and Data Sources
The wealth concept used is based upon national accounts and it is restricted to net household wealth, that is, the current market value of all nancial and non- nancial assets owned by the household sector net of all debts. For net nancial wealth, that is, for nancial assets net of liabilities, I rely on the latest and previous nancial accounts (European System of Accounts (ESA) 2010 and 1995, Bank of Spain) for the period 1996-2015 and 1984-1995, respectively. Financial accounts report wealth quarterly and I use mid-year values.
Households’ nancial assets include equities (i.e., stocks, investment funds and nan-cial derivatives), debt assets, cash, deposits, life insurance and pensions. Households’ nancial liabilities are composed of loans and other debts. It is important to mention that pension wealth excludes Social Security pensions, since they are promises of future government transfers. As stated in Saez and Zucman, 2016, including them in wealth would thus call for including the present value of future health care bene ts, future government education spending for one’s children, etc., net of future taxes. Hence, it would not be clear where to stop.
The wealth concept used only considers the household sector (code S14, according to the System of National Accounts (SNA)) and excludes non-pro t institutions serving households (NPISH, code S15). There are three reasons which explain this decision. First, due to lack of data, non-pro t wealth is not easy attributable to individuals. Second, income from NPISH is not reported in personal income tax returns. Third, non-pro t nancial wealth amounts to approximately 1-3% of household nancial wealth between 1995 and 2017 in Spain (Table B1). Hence, it is a negligible part of wealth and excluding it should not alter the results.
Spanish nancial accounts report nancial wealth for the household and NPISH sector and also for both households and NPISH isolated as separate sectors. However, the level of disaggregation of the balance sheets in the latter case is lower than in the case in which households and NPISH are considered as one single sector. For instance, whereas the balance sheet of the sector of households and NPISH distinguishes among wealth held in investment funds and wealth held in stocks, the balance sheet of the household sector only provides an aggregate value with the sum of wealth held in these two assets. In order to have one value for household wealth held in investment funds and one value for household wealth held in stocks, I assume that they are proportional to the values of households’ investment funds and stocks in the balance sheet of households and NPISH. For non- nancial wealth, it is not possible to rely on non- nancial accounts based on the SNA. Even though there are some countries that have these accounts, such as France and United Kingdom, no institution has constructed these type of statistics for Spain yet. I need to use other statistics instead. My de nition of household non- nancial wealth consists of housing and unincorporated business assets and I rely on the series elaborated by Artola Blanco, Bauluz, and Mart nez-Toledano, 2020. Housing wealth is derived based on residential units and average surface from census data on the one hand, and average market prices from property appraisals, on the other hand.8 Unincorporated business assets have been constructed using the ve waves of the Survey of Household Finances (2002, 2005, 2008, 2011, 2014) elaborated by the Bank of Spain and extrapolated backwards using the series of non- nancial.
Table of contents :
1 Long-Run Wealth Accumulation in Spain
1.1 Literature review
1.1.1 Long-run evolution of national wealth
1.1.2 Determinants of the increase in housing prices since the late 1990s
1.2 Concepts, methodology, and empirical estimate
1.3.1 Personal wealth
1.3.2 National wealth
1.4 International capital ows and housing prices
1.5 Concluding comments
2 Housing and Wealth Inequality in Spain
2.1 Concepts, Data and Methodology
2.1.1 Aggregate Wealth: Concept and Data Sources
2.1.2 Distribution of Wealth: The Mixed Capitalization-Survey Approach
2.2 House Price Cycles and the Wealth Distribution
2.2.1 Evolution of Real House Prices and Aggregate Household Wealth
2.2.2 Wealth Inequality Dynamics during Housing Booms and Busts
2.2.3 Determinants of Wealth Inequality Dynamics during Housing Booms and Busts
2.3 Nature of Asset-Specic Saving Responses
2.3.1 Portfolio Adjustment Frictions
2.3.2 Real Estate Market Dynamics
2.3.3 Tax incentives
2.4 Concluding comments
3 Wealth Taxation and Mobility in Spain
3.2 Institutional Details
3.3 Description of Data
3.3.1 Wealth Extrapolation Method
3.3.2 Tax Calculator
3.3.3 Treatment and Comparison Groups
3.4 Descriptive Evidence
3.5 Aggregate Analysis
3.6 Individual Choice Model
3.7 Implications for Revenue and Wealth Inequality
3.7.1 Revenue Analysis
3.7.2 Wealth Inequality Analysis
3.8 Concluding comments
A Long-run Wealth Accumulation in Spain
A.1.2 Asset classication
A.1.3 Time coverage
A.2 Domestic assets
A.2.1 Produced assets
A.2.2 Non-produced assets
A.3 Personal wealth
A.3.1 Non-nancial assets
A.3.2 Financial assets
A.4 General government wealth
A.4.1 Non-nancial produced assets: public capital
A.4.2 Non-nancial non-produced assets
A.4.3 Financial assets
A.5 Corporate wealth
A.5.1 Non-nancial assets of non-nancial corporations
A.5.2 Non-nancial assets of nancial institutions
A.5.3 Financial assets and liabilities
A.5.4 Tobin Q
A.6 Foreign wealth
A.7 Income and saving
A.7.1 National income
A.7.2 National savings and the current account balance
A.7.3 Decomposition of wealth accumulation
A.7.4 Interactions between international capital ows and housing prices
A.8 Additional robustness checks
A.8.1 Sensitivity of housing wealth series
A.8.2 Housing assets decomposed into land and structures: the residual approach
A.8.3 Alternative measurement of book-value national wealth
A.8.4 The decomposition of national wealth accumulation with the book-value approach and the private wealth sub-component .
A.8.5 Capital gains and asset price changes
A.8.6 Market vs. book-value wealth estimation
B Housing and Wealth Inequality in Spain
B.1 Imputation methods
B.1.1 Bottom of the income distribution
B.1.2 Assets that do not generate taxable income
B.2 The Spanish Personal Income Tax and Wealth Tax
B.2.1 A Recount of Personal Income Taxation in Spain
B.2.2 A Recount of Wealth Taxation in Spain
B.3 Accounting for Oshore Wealth
B.4 Robustness Checks on the Distribution Series
B.4.1 Comparison with Other Sources
B.4.2 Testing the Mixed Capitalization-Survey Method
B.5 Identifying Housing Booms and Busts
B.6 Wealth Distribution in Spain by Age
B.7 Wealth Mobility and Synthetic Saving Rates
B.8 Alternative Explanations to Saving Responses
B.8.1 Risk aversion
B.8.2 Financial Knowledge and Financial advising
B.8.3 Expectations on House Prices
B.9 Appendix Figures and Tables
C Wealth Taxation and Mobility in Spain 368
C.1.1 Institutions Appendix
C.1.2 Data Appendix