We model a reinsurance mechanism for the national unemployment insurance programs of euro area member states. The proposed risk-sharing scheme is designed to smooth country-level unemployment risk and expenditures around each country's median level, so that participation and contributions remain incentive-compatible at all times and there are no redistributionary transfers across countries. We show that, relative to the status quo, such scheme would have provided nearly perfect insurance of the euro area member states' unemployment expenditures risk in the aftermath of the 2009 sovereign debt crisis if allowed to borrow up to 2 percent of the euro area GDP. Limiting, or not allowing borrowing by the scheme, would have still provided significant smoothing of surpluses or deficits in the national unemployment insurance programs over the period 2000-2019.

I analyze the mapping between fundamental elements of financial contracts and transactions -- property rights, enforcement, commitment, information -- and the algorithmic tools and constraints of digital technologies such as blockchain platforms and automated (`smart') contracts. I then describe and formalize the microeconomic foundations, algorithmic building blocks, and possible uses of blockchain digital platforms for implementing constrained-optimal multiperiod contracts in incomplete markets settings with information or enforcement frictions and as collateral mechanism supporting on-platform and off-platform transactions and payments. Specific economic applications are provided and analyzed.

We analyze the economic determinants and dynamics of transaction fees in the Ethereum blockchain before and after two significant platform updates. The first is the August 2021 "London" upgrade, a switch from user-bid gas price (transaction fee per unit of complexity) to a fee model in which the gas price is formed as the sum of an algorithmically determined base fee and an optional priority fee (tip) chosen by the user. The second update ("the Merge") is the September 2022 switch from proof-of-work to proof-of-stake transactions validation. We estimate the impact on transaction fees of both demand factors (block utilization, transaction type, ETH price in USD) and algorithmic supply-side factors (the block gas limit and base fee). Using data from nearly 900 million blockchain transactions, we find that the gas price is statistically significantly positively associated with the block utilization rate. A larger share of contract call transactions or legacy (user-bid gas price) transactions is linked with higher gas prices on average. On the supply side, a higher block gas limit is statistically significantly associated with lower gas prices.

We formulate and solve a range of dynamic models of international capital flows and risk sharing with imperfect capital markets. We feature both models of exogenously incomplete markets (debt with tax on borrowing or on capital outflows, non-defaultable debt) and models with endogenously incomplete markets (defaultable debt, limited commitment), as well as the complete markets benchmark. All models share common preferences and technology. We use computational methods based on mechanism design, linear programming, and maximum likelihood to estimate and statistically test across the alternative models of international capital markets. Our methods work with cross-sectional or panel data and allow for measurement error and unobserved heterogeneity. We study which models fit best and also what type of data (income, investment, capital, consumption, or all together) can be used to distinguish across the alternative models. Empirically, we use panel data on GDP, government expenditure, consumption, capital stock and investment per capita for 175 countries in 1993-2002. We find that, overall, the defaultable debt and autarky models fit the data best. The complete markets and limited commitment models are rejected in all estimation runs.

We study a network-based model of criminal activity. Agents' payoffs depend on the number and structure of links among them and are determined in a Nash equilibrium of a crime effort supply game. Unlike much of the existing literature that takes network structure as given, we analyze optimal network structures, defined as maximizing aggregate payoff. Using potential functions, we give necessary and sufficient conditions that guarantee the existence and uniqueness of equilibria with non-negativity constraints on effort. These results can be used to identify optimal networks for given cost and benefit parameter configurations drawing on graph theory and using a computational algorithm that searches over all possible non-isomorphic networks of a given size. Our results can be also used to study, via numerical simulations, the effects of alternative crime reducing policies on the network structure and crime level - removing agents, removing links or varying the probability of apprehension.

The paper presents a stylized general equilibrium model of a developing economy in which the wealth distribution, the interest rate, and the wage rate are endogenous and interact dynamically. A credit market imperfection stemming from limited commitment results in allocative inefficiency due to credit rationing and occupational choice constraints. Credit rationing is shown to persist as the economy develops. The proposed model is shown to match both general empirical regularities pertaining to developing economies and macroeconomic data from Thailand. Furthermore, wealth inequality in this setting may be detrimental for economic development, providing a rationale for redistribution policies.

This paper provides a step-by-step hands-on introduction to the techniques used in setting up and solving moral hazard programs with lotteries using Matlab. It uses a linear programming approach due to its relative simplicity and the high reliability of the available optimization algorithms.