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Cristiano Ricci

Publications and source records attributed to Cristiano Ricci.

18 recordsLinked to original sources

Aggregation Bias in Proxy Measurement: Nighttime Lights and Local Economic Activity

This paper studies when high-resolution signals aggregated to administrative units can recover unobserved local economic activity. We develop a reverse-regression framework for signals generated by activity but used to predict it at coarser spatial supports. The main theorem decomposes predictive elasticity into elementary elasticity, reverse-regression attenuation, and a spatial aggregation term driven by unit size and within-unit dispersion, showing aggregation pulls elasticities toward one. Monte Carlo evidence confirms the decomposition and clarifies transferability conditions. Applications to VIIRS nighttime lights and local GDP or income in Brazil, Italy, the United States, Indonesia, and Kenya support local calibration mainly in richer contexts.

econ.EM↗

The invisible hand as an emergent property: a gradient flow approach

We develop a general equilibrium model in which, at each instant, a short-run competitive equilibrium arises. Heterogeneity in factor allocation generates differential profit rates across sectors, prompting firms to move between them under myopic profit-seeking behaviour, subject to quadratic reallocation costs. The aggregate dynamics of the economy can be formalised as a gradient flow in a Wasserstein space, starting from a partial differential equation that describes the reallocation of firms across sectors. Two key emergent properties arise: (i) decentralised and uncoordinated decisions can be reinterpreted as the solution to a sequence of global optimisation problems, involving a function of aggregate consumption, which increases monotonically along the dynamic path; (ii) the long-run competitive equilibrium is efficient, as the distribution of firms maximises aggregate consumption and profit rates are equalised across sectors. We extend the baseline model to incorporate non-symmetric preferences, intrasectoral externalities, a fixed cost of reallocation, and labour immobility. These extensions reveal conditions under which the efficiency and uniqueness of the long-run equilibrium may fail, but also highlight the surprising result that the decentralised equilibrium can remain efficient even in the presence of externalities. Finally, using a large sample of EU firms from the period 2018-2023, we empirically document convergence in sectoral profit rates, but not in labour productivity, pointing to a certain degree of labour immobility. We also find evidence suggesting the absence of significant fixed costs of reallocation at the sectoral level, the presence of positive but limited intrasectoral externalities, and a moderate degree of substitutability among goods.

econ.TH↗

The spatial evolution of economic activities and the emergence of cities

This paper examines the spatial agglomeration of workers and income in a continuous space-time framework. Local markets feature spatial spillovers and both exogenous and endogenous amenities. Workers relocate to maximise their instantaneous utility, constrained by mobility costs. In the limit of infinite workers, short-run equilibria are described by a partial differential equation (PDE). The PDE reveals spatial dynamics influenced by initial conditions, path dependence, and metastability (persistence), where prolonged stability is disrupted by sharp transitions to new distributions. We characterise conditions for spatial agglomeration in stationary equilibria and demonstrate that social utility consistently increases over time, suggesting efficient spatial allocations. Numerical results replicate key patterns, such as city formation, dependence on historical spatial patterns, and nonlinear out-of-equilibrium dynamics.

econ.TH↗

An integral transformation approach to differential games: a climate model application

We develop an Integral Transformation Method (ITM) for the study of suitable optimal control and differential game models. This allows for a solution to such dynamic problems to be found through solving a family of optimization problems parametrized by time. The method is quite flexible, and it can be used in several economic applications where the state equation and the objective functional are linear in a state variable. We illustrate the ITM in the context of a two-country integrated assessment climate model. We characterize emissions, consumption, transfers, and welfare by computing the Nash equilibria of the associated dynamic game. We then compare them to efficiency benchmarks. Further, we apply the ITM in a robust control setup, where we investigate how (deep) uncertainty affects climate outcomes.

econ.TH↗

The spatial evolution of economic activities: from theory to estimation

This paper studies the evolution of economic activities using a continuous time-space aggregation-diffusion model, which encompasses competing effects of agglomeration and congestion. To bring the model to the real data, a novel discretization technique over time and space is introduced. This technique effectively disentangles spatial effects into pure topography, agglomeration, repulsion, and diffusion forces, which is crucial for developing robust econometric methods in spatial economics. Our empirical analysis of personal income across Italian municipalities from 2008 to 2019 validates the model's primary predictions and demonstrates superior performance compared to the most common spatial econometric models in the literature.

econ.GN↗

Unveiling spatial patterns of population in Italian municipalities

We study the evolution of population density across Italian municipalities on the based of their trajectories in the Moran space. We find evidence of spatial dynamical patterns of concentrated urban growth, urban sprawl, agglomeration, and depopulation. Over the long run, three distinct settlement systems emerge: urban, suburban, and rural. We discuss how estimating these demographic trends at the municipal level can help the design and validation of policies contrasting the socio-economic decline in specific Italian areas, as in the case of the Italian National Strategy for Inner Areas (Strategia Nazionale per le Aree Interne, SNAI).

econ.GN↗

A non-invariance result for the spatial AK model

This paper deals with the positivity condition of an infinite-dimensional evolutionary equation, associated with a control problem for the optimal consumption over space. We consider a spatial growth model for capital, with production generating endogenous growth and technology of the form AK. We show that for certain initial data, even in the case of heterogeneous spatial distribution of technology and population, the solution to an auxiliary control problem that is commonly used as a candidate for the original problem is not admissible. In particular, we show that initial conditions that are non-negative, under the auxiliary optimal consumption strategy, may lead to negative capital allocations over time.

econ.TH↗

Epidemic Models as Scaling Limits of Individual Dynamics

Infection spread among individuals is modelled with a continuous time Markov chain, in which subject interactions depend on their distance in space. The well known SIR model and non local variants of the latter are then obtained as large scale limits of the individual based model in two different scaling regimes of the interaction.

math.PR↗

A Mean Field Game model for COVID-19 with human capital accumulation

In this manuscript we present several possible ways of modeling human capital accumulation during the spread of a disease following an agent based approach, where agents behave maximizing their intertemporal utility. We assume that the interaction between agents is of mean field type, yielding a Mean Field Game description of the problem. We discuss how the analysis of a model including both the mechanism of change of species from one epidemiological state to the other and an optimization problem for each agent leads to an aggregate behavior that is not easy to describe, and that sometimes exhibits structural problems. Therefore we eventually propose and study numerically a SEIRD model in which the rate of infection depends on the distribution of the population, given exogenously as the solution to the the Mean Field Game system arising as the macroscopic description of the discrete multi-agent economic model for the accumulation of human capital. Such model arises in fact as a simplified but tractable version of the initial one.

math.OC↗

Numerical computation of probabilities for nonlinear SDEs in high dimension using Kolmogorov equation

Stochastic Differential Equations (SDEs) in high dimension, having the structure of finite dimensional approximation of Stochastic Partial Differential Equations (SPDEs), are considered. The aim is to compute numerically expected values and probabilities associated to their solutions, by solving the associated Kolmogorov equations, with a partial use of Monte Carlo strategy - precisely, using Monte Carlo only for the linear part of the SDE. The basic idea was presented in Flandoli et al., JMAA (2020), but here we strongly improve the numerical results by means of a shift of the auxiliary Gaussian process. For relatively simple nonlinearities, we have good results in dimension of the order of 100.

math.PR↗

A mean-field approach to self-interacting network, convergence and regularity

The propagation of chaos property for a system of interacting particles, describing the spatial evolution of a network of interacting filaments is studied. The creation of a network of mycelium is analyzed as representative case, and the generality of the modeling choices are discussed. Convergence of the empirical density for the particle system to its mean field limit is proved, and a result of regularity for the solution is presented.

math.PR↗

On the relation between the Girsanov transform and the Kolmogorov equations for SPDEs

The Girsanov transform and Kolmogorov equations are two useful methods for studying SPDEs. It is shown that, under suitable conditions, the series expansion obtained from the Girsanov transform coincides with the one generated by an iteration scheme for Kolmogorov equations. We also apply the iteration approach to extend the well posedness theory for Kolmogorov equations beyond the boundedness condition on the nonlinear term.

math.PR↗

On the Macroscopic limit of Brownian Particles with local interaction

An interacting particle system made of diffusion processes with local interaction is considered and the macroscopic limit to a nonlinear PDE is investigated. Few rigorous results exists on this problem and in particular the explicit form of the nonlinearity is not known. The paper reviews this subject, some of the main ideas to get the limit nonlinear PDE and provides both heuristic and numerical informations on the precise form of the nonlinearity which are new with respect to the literature and coherent with the few known informations.

math.PR↗

A numerical approach to Kolmogorov equation in high dimension based on Gaussian analysis

For Kolmogorov equations associated to finite dimensional stochastic differential equations (SDEs) in high dimension, a numerical method alternative to Monte Carlo simulations is proposed. The structure of the SDE is inspired by stochastic Partial Differential Equations (SPDE) and thus contains an underlying Gaussian process which is the key of the algorithm. A series development of the solution in terms of iterated integrals of the Gaussian process is given, it is proved to converge - also in the infinite dimensional limit - and it is numerically tested in a number of examples.

math.PR↗

New particle representations for ergodic McKean-Vlasov SDEs

The aim of this paper is to introduce several new particle representations for \textit{ergodic} McKean-Vlasov SDEs. We construct new algorithms by leveraging recent progress in weak convergence analysis of interacting particle system. We present detailed analysis of errors and associated costs of various estimators, highlighting key differences between long-time simulations of linear (classical SDEs) versus non-linear (Mckean-Vlasov SDEs) process.

math.PR↗

The Navier-Stokes-Vlasov-Fokker-Planck system as a scaling limit of particles in a fluid

Convergence of a system of particles, interacting with a fluid, to Navier-Stokes-Vlasov-Fokker-Planck system is studied. The interaction between particles and fluid is described by Stokes drag force. The empirical measure of particles is proved to converge to the Vlasov-Fokker-Planck component of the system and the velocity of the fluid coupled with the particles converges in the uniform topology to the the Navier-Stokes component. A new uniqueness result for the PDE system is added.

math.PR↗

The Vlasov-Navier-Stokes equations as a mean field limit

Convergence of particle systems to the Vlasov-Navier-Stokes equations is a difficult topic with only fragmentary results. Under a suitable modification of the classical Stokes drag force interaction, here a partial result in this direction is proven. A particle system is introduced, its interaction with the fluid is modelled and tightness is proved, in a suitable topology, for the family of laws of the pair composed by solution of Navier-Stokes equations and empirical measure of the particles. Moreover, it is proved that every limit law is supported on weak solutions of the Vlasov-Navier- Stokes system. Open problems, like weak-strong uniqueness for this system and its relevance for the convergence of the particle system, are outlined.

math.PR↗

A mathematical model for growth of solid tumors and combination therapy with an application to colorectal cancer

We present a mathematical model, based on ordinary differential equations, for the evolution of solid tumors and their response to treatment. Specifically the effects of a cytotoxic agent and a monoclonal antibody are included as control term in the equations. The variables considered here are: the number of cancerous cells sensitive to chemotherapy, the number of cancerous cells resistant to chemotherapy, the degree of angiogenesis and the average intensity of VEGF. The rules that govern the quantities mentioned above are based on a geometrical argument: we approximate the tumor mass as a sphere and thus derive basic formulae for the normoxic cells and for VEGF production. The monoclonal antibody acts on VEGF and thus has in uence to the global degree of angiogenesis. Numerical estimates on some of the parameters are performed in order to match the main landmark in tumor progression and reaction to treatment in the specific case of colorectal cancer.

q-bio.TO↗