Communism and Financial Markets: Laudenbach, Malmendier & Niessen-Ruenzi (2026)

What this is. The paper’s core results, the identification strategy, and the empirical specifications with enough detail to know what it found and how, without reading all 43 pages. To replicate or extend, read the full source at the original.

TL;DR

Using three independent data sets (a representative survey of 9,695 Germans, proprietary bank records for 326,437 customers, and brokerage data for 230,229 retail investors), the paper shows that East Germans are 25-28% less likely to participate in the stock market than West Germans, and that a significant gap of roughly 10% persists after controlling exhaustively for wealth, income, financial literacy, trust, social capital, and risk aversion. Where prior work such as Fuchs-Schundeln and Haliassos (2021) documents the East-West participation gap, this paper shows that a residual gap survives richer controls and traces it to ideology. The paper argues that the gap is explained by lasting adherence to the GDR’s anti-capitalist ideology: East Germans with stronger positive experiences of life under communism (proxied by geography-based variation and by survey memories) show greater stock-market aversion, while those with more negative experiences (e.g., living in heavily polluted areas or areas without Western TV access) invest more. The financial cost is real: East German investors earn 7-11 basis points per month less, hold fewer assets, pay higher fund fees, and hold less diversified portfolios than comparable West Germans.

Core results

Magnitudes and significance are as reported; **/*** = 5%/1%. Locators point into the source PDF.

#	Result	Locator	Magnitude
R1	Raw East-West gap in stock market participation is large and consistent across all three data sets	Table III, pp. 1119-1120; Table II, p. 1114	Survey: 27.6% gap (East 26.9% vs. West 35.5%); bank: 25.2% gap; broker: 27.7% gap
R2	A significant residual gap of ~10% remains after controlling for the full set of demographic and financial variables	Table III col (2) all panels, pp. 1119-1120	Survey: -0.026*** (SE 0.009), effect size 8.4%; bank: -0.007*** (SE 0.001), 7.7%; broker data: -0.156*** (SE 0.002), 19.1%
R3	East Germans who moved to West Germany after Reunification and now live in the same economic environment as West Germans still invest significantly less	Table IV col (1)-(2), p. 1125	Survey movers: -0.072*** (SE 0.026) on all Germans, -0.075** (SE 0.029) restricting to West Germans only
R4	East Germans are less willing to buy “capitalist” stocks (financial firms, U.S. firms) and more willing to buy stocks of formerly communist countries	Table V, p. 1130	Survey: -1.9 pp for financial firms (4.7% relative gap), -1.9 pp for U.S. firms (5.5% gap); +5.9 pp for Chinese firms (23.5% gap); broker data: -4.9 pp financial firms***, -1.9 pp U.S. firms***, +0.4 pp East European firms***
R5	Within East Germany, anti-capitalist and anti-stock-market attitudes directly predict lower stock market participation	Table VI, p. 1132	”I generally reject stocks”: -0.103*** (SE 0.004); “Investing in stocks is immoral”: -0.070*** (SE 0.006); “Capitalism should be abolished”: -0.020*** (SE 0.005)
R6	Negative GDR experiences (pollution, no Western TV access) predict higher stock market participation; positive experiences (renamed showcase cities, Olympic gold medal wins) predict lower participation	Table VII, p. 1136	Pollution: +0.058*** (SE 0.009); No West-TV: +0.090*** (SE 0.016); Renamed city: -0.169*** (SE 0.010); Olympic gold (population-weighted): -0.044*** (SE 0.006)
R7	Survey-based GDR memories directly link to stock market participation in the expected direction	Table VIII, p. 1138	High GDR life standard: -0.032*** (SE 0.008); Wishing GDR back: -0.062*** (SE 0.016); Positive GDR memories: -0.050*** (SE 0.019)
R8	East German investors earn lower risk-adjusted portfolio returns than West Germans	Table IX Panel A, p. 1140	CAPM alpha (equal-weighted long East, short West): -0.082** (SE 0.040); FF3 alpha: -0.070* (SE 0.040); FF4 alpha: -0.099** (SE 0.041) per month
R9	East German investors hold significantly fewer passive investments, fewer assets, pay higher fund fees, and hold less diversified portfolios	Table IX Panel B, p. 1141	Passive investments: -0.017*** (SE 0.002), 44.7% lower relative to baseline; fund fees: +3.78% higher (col 3); number of assets: -33.1% (col 2)
R10	The stock market participation gap did not exist before the separation of Germany (1920-1924 bank data), ruling out pre-existing persistent differences	§II.A, p. 1116	Historical stock-market participation: East 66.7% vs. West 68.2%; difference not statistically significant (t-statistic: 0.34)

Overall (paper’s conclusion). Exposure to anti-capitalist ideology can exert lasting influence on individual investment behavior for years and even decades. Individuals who remember life in the GDR positively are more likely to continue holding anti-capitalist views and to refrain from stock market investment, with adverse financial consequences. Negative personal experiences under communism reverse the effect. These findings suggest that ideology, not only financial experience, shapes long-run investment behavior, and offer a micro-level foundation for macroeconomic growth differentials between formerly communist and capitalist countries. The broader context for this East-West comparison is the review of the long-term effects of communism in Eastern Europe by Fuchs-Schundeln and Schundeln (2020).

Theory / model

The paper has no formal model. The theoretical framework is the emotional-tagging hypothesis from cognitive science, applied to ideological formation. The core logic is as follows.

Emotionally charged stimuli are encoded more strongly in long-term memory. The valence (positive vs. negative) of an emotional context during an experience shapes the memory trace: positive emotions create favorable associations with the context, and negative emotions create unfavorable ones (Richter-Levin and Akirav, 2003; Dolan, 2002). This extends the experience-effects framework of Malmendier and Nagel (2011), in which lifetime returns shape stock market participation, to ideological rather than financial experiences. Applied to the GDR setting, individuals who lived under communism with positive experiences are predicted to (i) form stronger positive associations with the communist ideology and its anti-capitalist stance, (ii) retain these associations in long-term memory, and (iii) carry them into financial behavior decades later. Those with negative experiences are predicted to reject the ideology and, as a result, embrace capitalist financial markets more readily.

The tested hypothesis is:

• H1 (positive tagging): East Germans with more positive experiences under communism show greater adherence to anti-capitalist views and lower stock market participation.
• H2 (negative tagging): East Germans with more negative experiences under communism show less adherence to anti-capitalist views and higher stock market participation.
• H3 (mechanism): The link from experience to investment runs through ideological attitudes: anti-capitalist beliefs (toward stocks specifically and capitalism generally) mediate the effect on stock market participation.

Identification strategy. The paper uses three complementary identification approaches:

1. East-West comparison (Sections II-III): the quasi-natural experiment of Germany’s post-WWII division and 1990 reunification. Pre-trends are addressed using historical 1920-1924 bank data showing no pre-existing gap. Movers (East Germans who relocated to West Germany after Reunification) are used to rule out contemporaneous environmental confounders, addressing the concern raised by Becker, Mergele, and Woessmann (2020) that reunification may not be a clean natural experiment.

2. Within-East survey variation (Section III.B): variation in anti-capitalist attitudes among East Germans, related directly to stock market participation via logit regressions.

3. Within-East geographic variation (Section IV): four geography-based, predetermined (pre-reunification) proxies for positive or negative GDR experiences - pollution levels (negative), access to West German TV (negative for lack thereof, following Bursztyn and Cantoni (2016), who use Western TV access in East Germany as a quasi-exogenous proxy), living in GDR renamed showcase cities (positive), and proximity to Olympic gold medal winners (positive) - are used as quasi-exogenous instruments for emotional tagging. These proxies are orthogonal to current economic conditions and to each other (Internet Appendix Table IA.XIV).

Method

The paper applies logit regression as the primary estimator for all stock market participation outcomes. For portfolio characteristics and returns, OLS is used. The estimating framework is described in Section II.B (p. 1118).

Main logit specification (equation 1, p. 1118):

$$P(y_{it} = 1 \mid \text{East}_i, x_{it}, z_{c(i),t}, v_t) = \Phi(\alpha + \beta \cdot \text{East}_i + \gamma' x_{it} + \delta' z_{c(i),t} + v_t)$$

where:

• $y_{it}$ = 1 if investor $i$ participates in the stock market in year $t$
• $\text{East}_i$ = 1 if investor lives in East Germany (former GDR)
• $x_{it}$ = individual-level controls (gender, age, marital status, risk tolerance, wealth, income, financial literacy, trust, social capital, return expectations, peer effects; data-set specific)
• $z_{c(i),t}$ = municipality-level controls (in broker data: number of bank branches, population, real estate wealth, share with high-school degree, county GDP, number of local firms, Facebook social connectedness index)
• $v_t$ = year fixed effects (broker data only)
• $\Phi(\cdot)$ = logistic CDF (the paper’s notation for the logit link function)

Coefficients are reported as average marginal effects. Standard errors are clustered by municipality in the survey and bank data; by broker customer in the broker data.

The builds-on technique primitives used are panel-regression (OLS for returns and portfolio characteristics), logit-regression (the logit AME specification for participation), difference-in-differences (East-West comparison before/after, with matched-city and Berlin sub-samples), and matching (characteristics-matched cities: Eisenach vs. Bad Hersfeld, broker data col (4) Table III Panel C).

Alternative estimation. The paper also uses Conley (1999, 2008) spatial HAC standard errors with a 50 km distance cutoff and a two-year linear Bartlett window (§II.C) to address spatial and serial autocorrelation in the broker data. Results are qualitatively unchanged.

Empirical specifications

Baseline East-West participation gap (R1, R2)

Three separate logit regressions are run on each of the three data sets (Table III, pp. 1119-1120):

$$P(\text{stock market participant} = 1) = \Phi(\alpha + \beta \cdot \text{East}_i + \text{controls})$$

• Survey data (Panel A): N = 9,695; cross-section, 2023; SE clustered by municipality. Controls include gender, age, marital status, wealth (8-level), income (6-level), education (4-level), trust, risk tolerance (1-7), financial literacy (0-3), familiarity with stocks, peer effects, social capital (two measures), return expectations. Berlin excluded.

• Bank data (Panel B): N = 326,437; cross-section, 2019; SE clustered by municipality. Controls include gender, age, marital status, employment, wealth, income, risk tolerance, product ownership (consumer credit, retirement savings plans, credit card, mortgage, savings plans), number of consultations.

• Broker data (Panel C): N = 839,292 investor-years, June 2004-December 2012; SE clustered by broker customer. Controls include investor age, marital status, portfolio value, time account open, municipality controls (see above); year FE.

Robustness variants: (i) Berlin-only subsample (col 3, Panel C), (ii) matched cities Eisenach-Bad Hersfeld (col 4, Panel C, N = 574), (iii) restricting to active bank accounts (col 3, Panel B), (iv) single-stock holding as dependent variable (col 4, Panel B), (v) HAC standard errors.

Movers specification (R3)

$$P(\text{stock market participant} = 1) = \Phi(\alpha + \beta_1 \cdot \text{Mover}_i + \beta_2 \cdot \text{East}_i + \text{controls})$$

where $\text{Mover}_i$ = 1 if respondent moved from East to West Germany after 1989 and lived in GDR for at least 10 years. The $\text{East}_i$ coefficient is set to zero in columns (2) and (4) (West-Germans-only subsample). Estimated on survey data (col 1-2, N = 9,695/4,409) and a bank survey subsample (col 3-4, N = 241/198). Table IV, p. 1125.

Stock type preference: “communist” vs. “capitalist” stocks (R4)

$$P(\text{hold stock type } k = 1) = \Phi(\alpha + \beta \cdot \text{East}_i + \text{controls})$$

run separately for financial-industry stocks, U.S.-company stocks, Chinese stocks, and East European stocks. Survey: willingness to buy (Table V Panel A, p. 1130); bank data: actual holdings conditional on participating (N = 29,768, Table V Panel B); broker data: portfolio share (N = 611,410, Table V Panel C). Year FE included in broker data. SE clustered by municipality (survey, bank) or broker customer (broker data).

Anti-capitalist attitudes and participation (R5)

$$P(\text{stock market participant} = 1) = \Phi(\alpha + \beta \cdot \text{Attitude}_{qi} + \text{controls})$$

estimated separately for each of nine attitude survey questions on four-point Likert scales, restricted to the East German survey subsample (N = 5,286). Questions span (i) anti-stock-market attitudes (Panel A), (ii) anti-capitalist attitudes (Panel B), and (iii) pro-capitalist attitudes (Panel C). Table VI, p. 1132. SE clustered by municipality.

Geographic experience proxies and participation (R6)

$$P(\text{stock market participant} = 1) = \Phi(\alpha + \beta_k \cdot \text{Proxy}_k + \text{controls} + \text{year FE})$$

run separately for each of four proxy variables on the East German broker subsample (N = 171,343 investor-years):

• $\text{Pollution}_c$ = 1 if investor lives in a municipality on the 1990 GDR environmental emergency list (negative experience proxy)
• $\text{NoWestTV}_c$ = 1 if municipality did not receive West German TV signals (negative experience proxy)
• $\text{RenamedCity}_c$ = 1 if municipality was renamed under the GDR communist regime (positive experience proxy)
• $\text{OlympicGold}_c$ = indicator scaled by inverse population rank for whether an Olympic gold medal winner was born in the same municipality (positive experience proxy)

Table VII, p. 1136. SE clustered by broker customer.

GDR memories and participation (R7)

Same specification as R6 but using survey self-reports for five GDR memory questions (Likert scale): living standard, wishing GDR back, disappointed in FRG, positive GDR experience, positive GDR memories. East German survey subsample only (N = 1,661-4,874). Table VIII, p. 1138. SE clustered by municipality.

Portfolio return and characteristic regressions (R8, R9)

$$\alpha_{E\text{-}W,\, t} = \text{Long East portfolio} - \text{Short West portfolio}$$

Monthly portfolio returns (including dividends, from Thomson Reuters Datastream) are regressed on CAPM, Fama-French three-factor, and Carhart four-factor models using German risk factors (CFR Cologne). Both equal- and value-weighted portfolio constructions used. N = 92 monthly observations. Table IX Panel A, p. 1140.

Portfolio characteristics (passive investment indicator, number of assets, fund fees, Herfindahl index, bank-owned product share) regressed on East dummy plus the same broker-data controls. N = 515,600-839,292. Table IX Panel B, p. 1141.

Datasets used

Dataset	Role in paper	Wiki page
Bilendi online survey (2023)	Representative survey of 9,695 Germans (5,286 East, 4,409 West); attitudes, stock market participation, demographics, trust, risk tolerance	no page yet
Proprietary bank data (2019)	326,437 randomly selected bank customers; financial product holdings, wealth, income, stock market participation	no page yet
Online broker data (2004-2012)	839,292 investor-year observations for 230,229 retail investors; security holdings, portfolio characteristics, returns	no page yet
Thomson Reuters Datastream	Monthly stock returns (including dividends) for portfolio return calculations; merged into broker data	no page yet
SAVE survey (Germany)	Municipality-level real estate wealth panel, merged as control into broker data	no page yet
German Census / Federal Statistical Office	Education variables (share with high-school degree) and economic indicators at municipality level	no page yet
GDR 1990 Environmental Emergency Report	Municipality-level air-pollution indicator (18 GDR municipalities requiring immediate action)	no page yet
Braggion, von Meyerinck & Schaub (2023) bank data (1920-1924)	Historical baseline: stock market participation for 2,000+ East and West German customers before the GDR, to rule out pre-existing differences	no page yet

Sample: survey 2023 (cross-section); bank 2019 (cross-section); broker June 2004-December 2012 (panel). Geographic scope: Germany (East former GDR vs. West FRG). The broker data cover 171,343 East German investor-year observations used in the within-East experience analysis.

When to read the full paper

Read the original if you are: studying the long-run behavioral effects of political or ideological exposure on financial markets; replicating the geography-based experience proxies (pollution, West-TV access, renamed cities, Olympic victories); designing surveys to measure ideology and financial behavior jointly; or studying the financial welfare costs of ideological aversion to capital markets. The Internet Appendix contains all robustness tables (IA.III-IA.XV), variable definitions (Table IA.I), and the exact survey question wording (Table IA.X).

Attribution and rights

Source: peer-reviewed, The Journal of Finance 81(2), April 2026, pp. 1103-1145. DOI: 10.1111/jofi.70006. Copyright 2025 the American Finance Association. This article is paywalled; no Creative Commons licence is in effect.

This distillation was extracted by an LLM (claude-sonnet-4-6) on 2026-06-01 and is not human-verified or independently reproduced. Access to the full text requires a subscription to The Journal of Finance or institutional access via Wiley Online Library.

Laudenbach, Christine, Ulrike Malmendier, and Alexandra Niessen-Ruenzi. “The Long-Lasting Effects of Experiencing Communism on Attitudes toward Financial Markets.” The Journal of Finance 81, no. 2 (April 2026): 1103-1145. DOI: 10.1111/jofi.70006.