Property rights, fiscal capacity, and social capacity: The lasting impact of the Taiping Rebellion

Layer 1: Overview

Research question and motivation: How do civil wars affect long-term development, and through which institutional mechanisms? The paper studies the Taiping Rebellion (1850-1864) in Qing China, one of history’s deadliest civil wars (at least ~20 million deaths, with some estimates of 70-100 million), as a critical juncture in China’s path to modernity. It matters because the rebellion generated large, persistent regional institutional variation that can help explain what the authors call the “Intra-China Divergence” — regional GDP-per-capita gaps as large as 27-to-1 (Dongguan vs. Tianshui, 2010) that rival the world’s largest inter-regional gaps.

Data and design: A prefecture-level (occasionally county-level) panel covering 266 prefectures in China proper (1820 delineation). 55 prefectures fell under Taiping control (treatment) — split into 37 “Early Taiping” prefectures (occupied up to 1859, in Anhui/Jiangxi/Hubei, ambiguous land rights) and 18 “Late Taiping” prefectures (occupied from 1860, in Jiangsu/Zhejiang, stronger land rights) — and 211 control prefectures. Population is observed at seven points (1820, 1851, 1880, 1910, 1953, 1982, 2000). The core strategy is difference-in-differences (1820 reference year, prefecture and year fixed effects), supplemented by propensity-score matching (135-prefecture matched sample), a spatial autoregressive (SAR) model, and an instrumental-variable strategy using the longitude of the prefectural seat (motivated by the Taiping Navy’s eastward-along-the-Yangtze military strategy; first-stage F-statistics above 20).

Main quantitative findings (with scope conditions): (1) Population: The rebellion caused large, permanent population losses. The Taiping DID coefficient is -0.45 in 1880 (a 36% lower population growth rate vs. control) and -0.51 in 1953 (40% lower) — no convergence. Crucially, in the matched sample Late Taiping areas recovered (no significant long-run population gap vs. control) while Early Taiping areas did not (an immediate ~30% drop in 1880 plus further decline). (2) Property rights: In 1915 county data, the idle-land share is 3.6 percentage points higher in Early Taiping than control counties, while Late Taiping is not significantly different from control — supporting the property-rights hypothesis. (3) Fiscal capacity (likin): Taiping areas collected ~12 times (e^2.5) as much likin per 1,000 sq km as control areas in 1869-1879, still 3.7 times as much in 1922-1925. Late Taiping areas had even higher intensity (22.2x in 1869-1879; 6.1x in 1922-1925) than Early Taiping (9.0x; 2.7x). (4) Social capacity (charities): On average the rebellion had no significant effect, but Late Taiping areas saw charity growth ~56 percentage points (44 log points) above control by 1880, rising to ~78 percentage points (58 log points) by mid-20th century. (5) Long-term development: Driven entirely by Late Taiping areas — 1982 agricultural+industrial output per capita 90% higher (64 log points), 2010 GDP per capita 87% higher (63 log points), and 2010 fiscal revenue per capita 203% higher (111 log points) than control; Early Taiping is statistically indistinguishable from control. Late Taiping counties also show higher post-1895 industrial firm entry. (6) Civic outcomes and resilience: Using CGSS 2010, Late Taiping residents show higher trust in personal networks and greater civic engagement (political attention, local participation). During the Great Famine (1959-1961), Taiping areas had 6.9% larger survivor cohorts; the effect is 28% stronger in Late Taiping (8.4%) than Early Taiping (6.5%).

Implications: Violent conflict can leave lasting positive institutional imprints — through property rights, decentralized local fiscal capacity (“war made the state” at the local level), and elite-led social capacity — conditional on favorable initial conditions (strong gentry, wealthier commercial regions). The authors argue cultivating civil society and social capacity could yield large payoffs given China’s strong-state/weak-society configuration.

Layer 2: Deep Dive

What is the core identification strategy and what are the main threats to it?

The baseline is a difference-in-differences comparing Taiping vs. control prefectures over 1820-2000, with prefecture and year fixed effects and 1820 as the reference year. Identification rests on parallel pre-trends: the Taiping coefficient in 1851 (pre-rebellion) is small and insignificant, indicating no differential selection conditional on controls. The main threats are: (i) the binary Taiping measure aligning with provincial boundaries and picking up broad regional dynamics; (ii) control-group contamination because some control prefectures were temporarily conquered (but not governed) by the Taiping Army; (iii) spatial spillovers between neighbors (Tobler’s law / Kelly 2019 critique); (iv) omitted subsequent historical events; and (v) omitted variables differing systematically between treated and control areas. The authors address these with dosage measures (battles, occupation months), matching, a SAR model, an IV (longitude), explicit controls for the Taiping conquest, an adjacent-treatment indicator, leave-one-province-out checks, and controls for many other historical events.

How does the instrumental-variable strategy work and why might longitude be valid?

Longitude of the prefectural seat instruments for the Taiping dummy. Relevance: the Taiping leaders’ July 1852 military plan was to march eastward along the Yangtze, capture Jiangning (Nanjing), and expand from there using their dominant navy — so eastern (higher-longitude) prefectures were far more likely to fall under Taiping rule (Table 1 confirms Taiping prefectures have significantly larger longitudes; first-stage F-statistics above 20, Shea’s partial R-squared above 0.1). Exclusion: prefecture fixed effects absorb time-invariant geographic advantages, and year-dummy interactions with key geography (distances to coastline, Grand Canal, Yangtze) allow flexible time-varying geographic effects; conditional on these, longitude is argued to be excludable. IV estimates are larger in magnitude than OLS but qualitatively confirm a persistent negative population effect (robust to Anderson-Rubin weak-IV inference). The authors caution that omitted determinants correlated with longitude cannot be fully ruled out.

What are the four hypotheses and how are they distinguished empirically?

(1) Property-rights hypothesis: Late Taiping areas (post-1860 ‘direct tenant payment’ system creating de facto/de jure tenant ownership) had better-defined land rights than Early Taiping areas (collapsed landlord system, lost deeds, anti-rent movements), so should have less idle land and faster population recovery — tested via the 1915 idle-land cross-section and the Early-vs-Late population DID. (2) Likin-as-fiscal-capacity hypothesis: Qing fiscal decentralization and the likin tax (introduced 1853) strengthened local fiscal capacity, persistently higher in Taiping (especially Late Taiping) areas — tested via the likin-intensity DID. (3) Social-change hypothesis: elite-led militias and reconstruction spurred charities (‘benevolent halls’/shantang) as bridging social capital, especially in Late Taiping areas — tested via charity-stock DID and by adding charities as a mediator in long-term regressions. (4) Social-cohesion-and-civic-engagement hypothesis: forged social capital persists, raising modern trust/civic engagement and reducing Great Famine deaths — tested via CGSS 2010 and famine-survivor cohort ratios.

What heterogeneity is documented?

The central heterogeneity is Early vs. Late Taiping. Early Taiping areas (Anhui/Jiangxi/Hubei) suffered permanent population loss, higher idle land (+3.6pp), only modest likin gains, no charity growth, no long-term development advantage, and weaker famine resilience. Late Taiping areas (Jiangsu/Zhejiang) recovered population, had no excess idle land, far higher likin intensity (22x early period), large charity growth (+56 to +78pp), strong long-term development gains (90%/87%/203% in output/GDP/fiscal revenue), higher modern trust and civic engagement, and the strongest famine resilience (8.4% vs 6.5%). Industrialization heterogeneity is also temporal: no Early/Late firm-entry difference before 1895, but after the 1895 Treaty of Shimonoseki liberalized private industry, Late Taiping counties had more entry and Early Taiping fewer.

What robustness checks are run?

For the population results: dosage interactions (log battles, log occupation months); excluding six most-intense-fighting prefectures (Wuchang, Songjiang, Anqing, Jiangning, Suzhou, Hangzhou); controlling for newly selected jinshi (civil-service quota channel); a SAR spatial model (after Pesaran cross-sectional-dependence tests); PSM matched sample; longitude IV with Anderson-Rubin inference; controls for seven other historical events (Guangxu Drought, Hui Revolt, Nian Rebellion, early-Republic conflicts, Sino-Japanese War, Chinese Civil War, missionary activity); explicit controls for Taiping conquest vs. regime; an adjacent-treatment indicator (Butts 2021) for spillovers; and leave-one-province-out exclusion. Long-term development results add SAR, matching, historical-event controls including the Cultural Revolution, and an ‘intermediate-term’ 1930s industrialization check. Famine results are robust to alternative famine-severity measures, SAR, matching, and historical-event controls.

How is the mediation analysis handled and what does it show?

The authors add likin intensity (1880) and average charities (1880-1941) to cross-sectional long-term regressions, explicitly flagging these as endogenous ‘bad controls’ (Angrist-Pischke 2009; Imai et al. 2011) to be interpreted cautiously as descriptive mediation. Findings: a one-SD increase in likin intensity is associated with +1.7pp middle-school completion, +4.8pp literacy, +5.3% schooling, and +12.2% (11.5 log points) GDP per capita in 2010. A one-SD increase in charities is associated with +15% 1982 output, +20% 2010 GDP, and +55% 2010 fiscal revenue per capita. Once charities are netted out, Late Taiping advantages in output, GDP, and fiscal revenue are attenuated by about 17%, 14%, and 22% respectively — highlighting the social-capacity channel.

How does the Great Famine resilience result connect to the rebellion?

Famine severity is measured by ‘Famine Control’ = ratio of cohort size born during the famine (1959-1961) to cohort size born pre-famine (1954-1957) from the 1990 census 1% sample (higher = less severe). Taiping areas had a 6.9% larger survivor cohort than non-Taiping; the effect is 8.4% in Late Taiping vs. 6.5% in Early Taiping. Back-of-envelope, the Late Taiping experience would have ‘saved’ ~31,374 people in an average prefecture (17% of the 1959-1961 cohort) vs. ~24,145 (13%) for Early Taiping. Controlling for political radicalism (reverse party-member density, -1*PMD, after Yang 1996) does not change the result. The mechanism: higher social capital made local officials more sympathetic/less radical in grain procurement and citizens better able to act collectively (paralleling Cao-Xu-Zhang 2022 on clan density and Hu-Yao-You 2023 on home-county officials).

How does this paper relate to and differ from closely related prior work?

Prior Taiping studies examined narrower consequences: civil-service exam quotas (Li 2014), demographic and industrialization effects (Li and Ma 2016), migration and public goods (Hao and Xue 2017), and late-Qing power distribution (Bai, Jia, and Yang 2023). None addressed the rebellion’s enduring impacts on modern development, social trust, and Great Famine responses, nor the property-rights/fiscal-capacity/social-capacity mechanism triad. It complements Xue (2021) on Qing charities, generalized trust, and political participation, but extends to development outcomes. Against the European state-building literature (war strengthens central state capacity via centralization), this paper’s distinctive claim is that the Taiping Rebellion strengthened LOCAL fiscal capacity through DECENTRALIZATION, and expanded local social capacity that constrained the central state.

What are the policy implications and their scope conditions?

The benefits of war-induced institutions are conditional, not universal: they appeared chiefly in Late Taiping areas with a strong gentry class and favorable initial conditions for modern sectors (the wealthier, more commercial Lower Yangtze). The likin/fiscal-capacity benefits are explicitly stated to be conditional on strong gentry and good modern-sector initial conditions. The broad implication is that, given China’s very strong state but still weak society today, cultivating civil society and strengthening social capacity could yield particularly large long-term payoffs. The authors also caution (Appendix F.1) that likin could be distortionary taxation rather than fiscal capacity, arguing the fiscal-capacity interpretation is more relevant for long-term development.

What significant caveats does the paper acknowledge?

Long-term mechanisms cannot be exhaustively identified — likin and charities are endogenous outcomes, so mediation magnitudes are descriptive, not causal. History contains near-infinite interrelated events, so confounding cannot be fully eliminated (a fundamental limitation of all history-based work). The IV may have omitted correlates of longitude. Some 2SLS estimates for development outcomes were largely insignificant. The charity-stock measure assumes charities persisted once founded (no closure dates in the data). On property-rights persistence: using 2005 World Bank Enterprise Survey data they find no association between modern firms’ perceived property-rights protection and Taiping regimes, suggesting the channel works through income effects rather than persistence of property rights per se.

Key Concepts

Early vs. Late Taiping areas: Early Taiping = prefectures occupied by the rebels up to 1859 (Anhui, Jiangxi, Hubei), where the old landlord system collapsed and land rights stayed ambiguous; Late Taiping = prefectures occupied from 1860 (Jiangsu, Zhejiang), where the Taiping introduced a ‘direct tenant payment’ (作佃交粮) system and issued new deeds, granting tenants de facto/de jure ownership. This distinction is the paper’s central source of institutional variation.

Likin (lijin): A local tax on trade and commerce introduced in 1853 (a transit tax on travelling merchants’ goods plus a business tax on resident merchants), collected in a decentralized, province-specific way. In the paper it is the operational measure of local fiscal capacity (likin revenue per 1,000 sq km), not central state capacity.

Social capacity: In the paper’s sense, the ability of society to act collectively, constrain the state, and empower its members — operationalized empirically by the stock of local charity organizations (‘benevolent halls’/shantang) that functioned as bridging social capital across classes.

Likin-as-fiscal-capacity hypothesis: The claim that the rebellion-induced likin system durably raised LOCAL fiscal capacity (an instance of Tilly’s ‘war made the state’ operating locally rather than centrally), which improved public-goods provision and long-run development — conditional on strong gentry and favorable modern-sector initial conditions.

Stationary bandit (applied to Late Taiping rulers): Borrowing Olson (1993): in Late Taiping areas the consolidated, longer-horizon Taiping regime behaved like a stationary bandit, lowering effective tax rates, encouraging land registration, and securing tenant property rights to expand the tax base and promote production, unlike the looting/confiscation of the early stage.

Famine Control: The paper’s local famine-severity measure: the ratio of the cohort born during the Great Famine (1959-1961) to the cohort born pre-famine (1954-1957) in the 1990 census; a higher value means less severe famine and more survivors, and it is less vulnerable to government understatement of famine deaths.

Intra-China Divergence: The authors’ term for China’s persistent, very large regional disparities in economic performance (up to 27-to-1 in GDP per capita) despite all regions historically sharing similar Malthusian income levels — the macro puzzle the rebellion’s institutional legacy helps explain.