arXiv subjects

Fernando Toledo

Publications and source records attributed to Fernando Toledo.

4 recordsLinked to original sources

arXiv2026

Cheaper AI, More Informality? A Dual Labor Market Model for Developing Economies

This paper studies what happens when AI gets cheaper, with emphasis on the labor market outcomes, whether it creates formal jobs or whether it pushes workers into informality. We argue that the answer depends on the elasticity of substitution between imported AI capital and formal labor. We build a small open economy DSGE model with a dual labor market, imported AI capital, and country risk, calibrated to an economy where informality is pervasive. The same decline in AI prices produces sharply different labor-market outcomes depending on whether AI substitutes or complements formal workers. Under substitution, cheaper AI weakens formal labor demand and increases the role of the informal sector as an employment buffer. Under complementarity, it expands formal employment and amplifies output, wages, investment, and capital accumulation. The model therefore shows that AI can become either a source of displacement pressure or a driver of formal-sector expansion, depending on how it interacts with human labor.

econ.GN↗

arXiv2026

Algorithmic Intermediation and the International Transmission of U.S. Monetary Policy

This paper examines how algorithmic and AI-driven fund management shapes the international transmission of U.S. monetary policy to emerging markets. It argues that the key source of instability is not algorithmic intermediation itself, but the similarity of models across funds. When algorithms rely on similar signals and make correlated errors, their trades reinforce one another and intensify capital-flow responses during periods of stress. When models are diverse, errors offset each other and algorithmic investors can stabilize flows. The paper develops a two-region macro-financial framework and tests its central prediction using equity portfolio flows to nineteen emerging markets from 2000 to 2024. The evidence shows that algorithmic herding amplifies outflows after U.S. monetary shocks only in high-volatility regimes, while faster adjustment alone has no comparable effect. The results imply that policy should focus on preserving model diversity rather than limiting the size of non-bank intermediation.

econ.GN↗

arXiv2025

Implicit quantile preferences of the Fed and the Taylor rule

We study optimal monetary policy when a central bank maximizes a quantile utility objective rather than expected utility. In our framework, the central bank's risk attitude is indexed by the quantile index level, providing a transparent mapping between hawkish/dovish stances and attention to adverse macroeconomic realizations. We formulate the infinite-horizon problem using a Bellman equation with the quantile operator. Implementing an Euler-equation approach, we derive Taylor-rule-type reaction functions. Using an indirect inference approach, we derive a central bank risk aversion implicit quantile index. An empirical implementation for the US is outlined based on reduced-form laws of motion with conditional heteroskedasticity, enabling estimation of the new monetary policy rule and its dependence on the Fed risk attitudes. The results reveal that the Fed has mostly a dovish-type behavior but with some periods of hawkish attitudes.

econ.GN↗

arXiv2021

Global Financial Cycle, Commodity Terms of Trade and Financial Spreads in Emerging Markets and Developing Economies

We study the diffusion of shocks in the global financial cycle and global liquidity conditions to emerging and developing economies. We show that the classification according to their external trade patterns (as commodities' net exporters or net importers) allows to evaluate the relative importance of international monetary spillovers and their impact on the domestic financial cycle volatility -i.e., the coefficient of variation of financial spreads and risks. Given the relative importance of commodity trade in the economic structure of these countries, our study reveals that the sign and size of the trade balance of commodity goods are key parameters to rationalize the impact of global financial and liquidity conditions. Hence, the sign and volume of commodity external trade will define the effect on countries' financial spreads. We implement a two-equation dynamic panel data model for 33 countries during 1999:Q1-2020:Q4 that identifies the effect of global conditions on the countries' commodities terms of trade and financial spreads, first in a direct way, and then by a feedback mechanism by which the terms of trade have an asymmetric additional influence on spreads.

econ.GN↗