Tina Koziol

Across advanced democracies, mainstream parties have expanded housing interventions while housing affordability has continued to deteriorate and support for extreme parties has continued to rise. This paper argues that these outcomes are connected. Housing markets generate a distinctive pathway out of mainstream politics because they bundle three economic pressures that are usually studied separately: consumption stress through rents, asset exclusion through blocked homeownership, and intergenerational closure through unequal wealth transmission. A policy response aimed at only one channel therefore leaves the broader mechanism intact.

I develop a calibrated agent-based model of 30,000 German households distributed across 16 regions. The model is identified by Simulated Method of Moments using distributional, housing-market, and political-economy targets, including the 23 February 2025 German federal election, and is validated out of sample against UK Brexit voting patterns. The model reproduces the German wealth distribution and the aggregate AfD second-vote share at the calibration optimum. It also generates a large within-region renter-owner cleavage in mainstream exit: +0.28 in Germany and +0.23 in the UK validation, with common direction and magnitude across countries. A stripped HANK benchmark matches aggregate calibration anchors by construction but returns mechanical zero on the three structural relationships on which the paper relies.

Five counterfactual policy experiments show why single-instrument housing politics fails to reverse extreme-party momentum. Rent caps, supply restrictions, and transaction frictions reduce specific housing pressures, but none produces a peak in the vote-share trajectory within 25 periods under any leakage profile. Only a bundled intervention, combining housing policy with a capital-tax-funded transfer to the bottom half of the wealth distribution at OECD-typical redistributive intensity, produces a peak followed by decay. The implication is not that housing explains all extreme-party support. It is that the housing component of mainstream exit is bundled by structure and therefore requires a bundled policy response.

Comparable monetary expansions produced radically different inflation outcomes after the Global Financial Crisis and after 2020. The dominant explanations (supply shocks, fiscal support, expectations de-anchoring) treat the divergence as contingent on the shocks themselves. This paper offers a structural alternative: the two episodes are reconciled once housing is placed at the centre of the transmission mechanism and CPI shelter measurement is recognised as a symmetric lag operator that understates inflation on the way up and overstates disinflation on the way down.

The core contribution is a 5×2 transmission taxonomy: five macro-financial channels (credit supply, collateral valuations, rental-market pass-through, wealth effects, and mortgage cash-flow effects) mapped across two inflation regimes (post-GFC and post-2020). The taxonomy is organised around four institutional primitives that vary across advanced economies and jointly determine which channels fire in which regime: (i) CPI shelter construction (rental-equivalence vs. actual rents vs. house prices), (ii) mortgage-contract structure (fixed-rate vs. floating, recourse vs. non-recourse, prepayment penalties), (iii) housing supply elasticity, and (iv) outright homeownership rate.

Using a harmonised panel of twenty advanced economies, I show that cross-country heterogeneity in inflation outcomes is driven primarily by these four institutional features rather than by shock composition. The framework recasts cross-country divergence as structural rather than contingent, identifies which channels can be reactivated by policy, and produces testable predictions for the next expansion. A companion SUERF Policy Brief summarises the implications for inflation-targeting regimes.

This paper develops a mechanism-isolation framework to show that behavioural-finance and Fed-put explanations of financial instability are complementary rather than competing. I build a heterogeneous-agent asset-pricing model in which capitalists form sticky reference points for expected returns, choose portfolios under reference-dependent preferences, and transmit wealth-weighted disappointment into monetary policy through an asymmetric Taylor rule.

The framework decomposes the 1980–2020 U.S. low-rate episode into four interacting but empirically separable channels: loss aversion, reference dependence, political pressure, and endogenous anchor drift. The political-pressure coefficient is identified externally by Simulated Method of Moments using the Cieslak and Vissing-Jorgensen (2021) intermeeting return-and-rate asymmetry, rather than by the crash, wedge, or counterfactual moments the model seeks to explain.

Mechanism-isolation experiments show that the four channels operate on distinct margins. Loss aversion amplifies crash depth; reference dependence amplifies volatility; political pressure governs zero-lower-bound duration; and endogenous anchor drift is the larger driver of the wedge between capitalist return expectations and the floored policy rate. Removing political pressure reduces ZLB time by 44 percentage points, while fixing the historical return anchor reduces the expectation-rate wedge by 3.49 percentage points, more than the effect of removing political pressure.

Policy counterfactuals show that macroprudential leverage caps and central-bank reform operate on different parts of the mechanism. Leverage caps directly constrain the reach-for-yield channel and sharply reduce crash frequency and depth, while central-bank reform mainly reduces ZLB duration and raises the mean policy rate. Financial instability in low-rate environments is best understood not as the product of a single distortion, but as a feedback loop between sticky return expectations, loss-averse portfolio choice, and politically responsive monetary policy.

We develop an agent-based epidemiological model in which agents are nodes in a network, their physical interactions are time-varying edges, and each agent carries an epidemiological state drawn from the Susceptible–Exposed–Infected–Recovered (SEIR) compartments. Into this setting we introduce naive social learning in the sense of DeGroot (1974): agents form subjective beliefs about the prevalence and severity of the disease by repeatedly averaging signals received from their neighbours, and adjust their protective behaviour accordingly.

The model is calibrated to detailed data for Cape Town, South Africa. Incorporating social learning materially improves fit: the best-fit squared difference between modelled and observed excess fatalities drops from 19.34 to 11.40. More importantly, the qualitative behaviour differs from standard compartmental models: social learning both flattens and shortens the curves for infections, hospitalisations, and excess fatalities, whereas contact-rate or transmission-probability reductions flatten the curve at the cost of lengthening the epidemic.

The paper contributes a tractable framework for embedding heterogeneous belief formation into epidemic models and shows that the behavioural response to information is a first-order determinant of epidemic dynamics, separate from, and sometimes substituting for, formal non-pharmaceutical interventions.

Price shocks that propagate through the financial system present a significant risk to financial system stability. This study evaluates the vulnerability of South African banks' portfolios to price-mediated contagion over the past decade. Using longitudinal balance-sheet data from the ten largest banks (2010–2020), stress tests are triggered by price shocks on South African government bonds, a marketable asset held by all banks in the sample.

The analysis finds that second-order feedback effects from bank deleveraging remain modest, and that the concentrated structure of the South African banking sector contributes positively to shock absorption. Over the ten-year window, however, banks have gradually increased portfolio similarity, which has incrementally heightened exposure to the price-mediated contagion channel.