nep-cmp New Economics Papers
on Computational Economics
Issue of 2020‒09‒28
28 papers chosen by
Stan Miles
Thompson Rivers University

  1. Modelling policy induced manure transports at large scale using an agent-based simulation model By Schaefer, David; Britz, Wolfgang; Kuhn, Till
  2. How market intervention can prevent bubbles and crashes By Rebecca Westphal; Didier Sornette
  3. A Global Economy Version of QUEST: Simulation Properties By Matthias Burgert; Werner Roeger; Janos Varga; Jan in 't Veld; Lukas Vogel
  4. The econ impact of projected affordable housing dev: does supply side matter? By Stephen Boyle; Kevin Connolly; Peter G McGregor; Mairi Spowage
  5. Das dynamische Mikrosimulationsmodell microDEMS zur Analyse der ökonomischen Integration von Immigrantinnen und Immigranten in Österreich By Martin Spielauer; Thomas Horvath; Marian Fink
  6. Estimating DSGE Models: Recent Advances and Future Challenges By Jesús Fernández-Villaverde; Pablo A. Guerrón-Quintana
  7. Machine learning techniques for strawberry yield forecasting By Li, Sheng; Wu, Feng; Guan, Zhengfei
  8. validarcae: Utility tool to deal with the Portuguese classification of economic activities (CAE) By Marta Silva
  9. Prévision de l’activité économique au Québec et au Canada à l’aide des méthodes Machine Learning By Philippe Goulet Coulombe; Maxime Leroux; Dalibor Stevanovic; Stéphane Surprenant
  10. Deep Learning, Predictability, and Optimal Portfolio Returns By Mykola Babiak; Jozef Barunik
  11. Liquidity Usage and Payment Delay Estimates of the New Canadian High Value Payments System By Francisco Rivadeneyra; Nellie Zhang
  12. Simulation Methods for Robust Risk Assessment and the Distorted Mix Approach By Sojung Kim; Stefan Weber
  13. Tactical planning of sugarcane harvest and transport operations By Aliano Filho, Angelo; Melo, Teresa; Pato, Margarida Vaz
  14. The use of rush deliveries in periodic review assemble-to-order systems By Mohammed Hichame Benbitour; Evren Sahin; Yves Dallery
  15. The COVID19-Pandemic in the EU: Macroeconomic Transmission and Economic Policy Response By Philipp Pfeiffer; Werner Roeger; Jan in ’t Veld
  16. How Do Voters Evaluate the Age of Politicians? By Charles McCLEAN; ONO Yoshikuni
  17. To Be or Not to Be? The Questionable Benefits of Mutual Clearing Agreements for Derivatives By Magdalena Tywoniuk
  18. A graphical approach to carbon-efficient spot market scheduling for Power-to-X applications By Neeraj Bokde; Bo Tranberg; Gorm Bruun Andresen
  19. The Fractured-Land Hypothesis By Jesús Fernández-Villaverde; Mark Koyama; Youhong Lin; Tuan-Hwee Sng
  20. Assessing the impacts of COVID-19 on household incomes and poverty in Myanmar: A microsimulation approach - An analytical summary [in Burmese] By Diao, Xinshen; Mahrt, Kristi
  21. Monetary policy with a state-dependent inflation target in a behavioral two-country monetary union model By Proaño Acosta, Christian; Lojak, Benjamin
  22. The Stable Transformation Path By Francisco J. Buera; Joseph P. Kaboski; Martí Mestieri; Daniel G. O'Connor
  23. Increasing Lab Capacity for Covid-19 Viral Testin By Francesco Flaviano Russo
  24. Uncertainty and Monetary Policy in Good and Bad Times: A Replication of the VAR Investigation by Bloom (2009) By Giovanni Caggiano; Efrem Castelnuovo; Gabriela Nodari
  25. COVID-19: Energy landscape theory of SARS-CoV-2 complexes with Particulate Matter By Zangari del Balzo, Gianluigi
  26. Considerations Regarding Inflation Ranges By Hess Chung; Brian M. Doyle; James Hebden; Michael Siemer
  27. Factor decomposition of changes in the tax base for income tax By Taro Ohno; Junpei Sakamaki; Daizo Kojima
  28. Income and Poverty in the COVID-19 Pandemic By Jeehoon Han; Bruce D. Meyer; James X. Sullivan

  1. By: Schaefer, David; Britz, Wolfgang; Kuhn, Till
    Abstract: ABMSIM, an agent-based model, is extended and applied to model short- and long-distance manure transports induced by the revised German Fertilization Ordinance (FO). It quantifies impacts on manure transports (max. 150 km), regional nutrient balances, and farm types, covering the farm population (~34,000 farms) of North Rhine-Westphalia, Germany (~35,000 km2). The large study area is realized by using an estimated meta-model based on simulation results with the detailed bio-economic farm model FarmDyn. Results indicate that manure exports increase due to FO measures related to P2O5 surpluses in pig farms, whereas increased transport distance is found in dairy and pig farms due to competition in the manure market. The study underlines that ABM applications for larger populations and landscapes are possible by reducing the computational load through meta-models. Future research can address improved meta-models based on econometric estimation or machine learning as well as feedback between manure market and its participants.
    Keywords: Environmental Economics and Policy, Farm Management, Research Methods/ Statistical Methods
    Date: 2020–09–17
  2. By: Rebecca Westphal (ETH Zürich - Department of Management, Technology, and Economics (D-MTEC)); Didier Sornette (ETH Zürich - Department of Management, Technology, and Economics (D-MTEC); Swiss Finance Institute; Southern University of Science and Technology; Tokyo Institute of Technology)
    Abstract: Using an agent-based model (ABM) with fundamentalists and chartists, prone to develop bubbles and crashes, we demonstrate the usefulness of direct market intervention by a policy maker, documenting strong performance in preventing bubbles and drawdowns and augmenting significantly the welfare of all investors. In our ABM, the policy maker diagnoses burgeoning bubbles by forming an expectation of the future return of the risky asset in the form of an exponential moving average of the excess return over the long-term return. The policy maker invests in the risky asset when he detects a small deviation of the return from the long-term growth rate in order to construct an inventory that he draws upon later to fight future market exuberance. Then, when this deviation between the current growth rate and the long-term growth rate exceeds the policy maker's tolerance level, he starts to sell the risky asset that he has accumulated earlier, in a countercyclical fight against future price increase. We find that the policy maker succeeds in preventing bubbles and crashes in our ABM. In simulations without bubbles, the policy maker behaves similarly to the fundamentalists and his impact is negligible, following the principle of "Primum non nocere". In simulations where bubbles form spontaneously as a result of the noise traders's strategies, the policy maker's intervention reduces the average drawdown by a factor of two when his market impact becomes significant. We find that the policy maker intervention improves all analysed metrics of market returns, including volatility, skewness, kurtosis and VaR, making the market less turbulent and more stable. The combination of fewer bubbles and crashes, lower market risks and the stability of the long-term growth rate make the policy maker intervention to improve the welfare of all investors as measured by their risk-adjusted return, increasing the Sharpe ratios from approximately 0.3 to 0.5 for noise traders, from 0.6 to 0.8 for fundamentalists as the market impact of the policy maker increases to the level of the fundamentalists. We also test the sensitivity of these results to variations of the key parameters of the strategy of the policy maker and find very robust outcomes. In particular, the conclusions are unchanged even under very large miscalibrated long-term expected returns of the risky asset.
    Keywords: financial bubbles, agent-based model, arbitrageurs, prediction, noise traders, fundamentalists, market intervention
    JEL: C53 C63 E58 E60 G01 G17 G18
    Date: 2020–08
  3. By: Matthias Burgert; Werner Roeger; Janos Varga; Jan in 't Veld; Lukas Vogel
    Abstract: This paper presents the structure and simulation properties of a core version of QUEST, an open-economy New Keynesian DSGE model developed and maintained by the European Commission. The multi-region model version with tradable goods, non-tradable goods and housing includes the euro area (EA), the nonEA EU plus the UK, the United States, Japan, Emerging Asia, and the rest of the world. The paper presents simulation results for a series of goods, factor, financial market, and policy shocks to illustrate how the structure of the model and its theoretical underpinnings shape the transmission of shocks to real and financial variables of the domestic economy and international spillover. In particular, the paper shows impulse responses for monetary policy, consumption, risk premia, productivity, credit, government spending, unconventional monetary policy and tariff shocks, and characterises their impact on real GDP, domestic demand components, trade, external balances, wages, employment, price levels, relative prices, interest rates, and public finances. While the scenarios are illustrative, they reflect important elements of the Global recession and the EA crisis (global risk shocks, private sector demand shocks and deleveraging) and of policy responses (fiscal policy, unconventional monetary policy) and challenges (protectionism) in recent years. In view of the macroeconomic conditions during this period, the paper shows simulations for an environment in which the zero lower bound on monetary policy is binding in addition to simulations under standard monetary policy.
    JEL: E37 E62 F47
    Date: 2020–06
  4. By: Stephen Boyle (Department of Economics, University of Strathclyde); Kevin Connolly (Department of Economics, University of Strathclyde); Peter G McGregor (Department of Economics, University of Strathclyde); Mairi Spowage (Department of Economics, University of Strathclyde)
    Abstract: A key current objective of Scottish policymakers is to increase the availability of affordable and social housing, with an expectation that this will have both societal and economic impacts. The purpose of this paper is to evaluate the potential economic impacts of meeting the projections of affordable housing needed in Scotland to combat homelessness. Typical economic impact assessments of social housing investment have focused exclusively on the effect of expenditures on demand, using input-output models (IO). However, recently some have argued that housing, like transport, should be treated as a type of infrastructure investment that is likely also to have potential supply side impacts – such as an increase in both labour supply and productivity. In this paper, we use both IO and Computable Generable Equilibrium (CGE) models to evaluate the economic impact of social housing investment, with a particular emphasis on the supply side impacts
    Keywords: Affordable housing, input-output, computable general equilibrium
    JEL: D58 E16 R13 R22
    Date: 2020–09
  5. By: Martin Spielauer (WIFO); Thomas Horvath; Marian Fink
    Abstract: Dieses Papier beschreibt den Aufbau und die Funktionsweise des dynamischen Mikrosimulationsmodells microDEMS zur Analyse der ökonomischen Integration von Immigranten und Immigrantinnen in Österreich. Dynamische Mikrosimulation bezeichnet die Simulation einer Bevölkerung, repräsentiert durch eine große Zahl von Individuen, über die Zeit. Simuliert werden neben demographischen Charakteristika wie Alter, Geschlecht und Herkunft verschiedene Aspekte individueller Lebensläufe wie Bildungs- und Erwerbskarrieren. microDEMS (Demographic Change, Employment and Social Security) ist ein am WIFO entwickeltes modulares dynamisches Mikrosimulationsmodell, welches für einen breiten Einsatzbereich in der österreichischen Wirtschaftsforschung konzipiert ist. Der Schwerpunkt dieses Papiers liegt in der Beschreibung jener Module, welche speziell zur Analyse der ökonomischen Integration von Immigrantinnen und Immigranten entwickelt wurden. microDEMS unterstützt die Erstellung von Szenarien zur Immigration nach Herkunft und Typ. Der individuelle (und elterliche) Immigrationshintergrund beeinflusst zahlreiche modellierte Verhalten wie Ausbildungskarrieren, Arbeitsmarktbeteiligung und Emigration. Das Modell erlaubt die Analyse der langfristigen Effekte alternativer Szenarien der Bildungs- und Erwerbsintegration von Immigrantinnen und Immigranten auf die soziodemographische Struktur der in Österreich lebenden Bevölkerung.
    Keywords: Microsimulation, Immigration, Bildung, Erwerb
    Date: 2020–09–08
  6. By: Jesús Fernández-Villaverde; Pablo A. Guerrón-Quintana
    Abstract: We review the current state of the estimation of DSGE models. After introducing a general framework for dealing with DSGE models, the state-space representation, we discuss how to evaluate moments or the likelihood function implied by such a structure. We discuss, in varying degrees of detail, recent advances in the field, such as the tempered particle filter, approximated Bayesian computation, the Hamiltonian Monte Carlo, variational inference, and machine learning, methods that show much promise, but that have not been fully explored yet by the DSGE community. We conclude by outlining three future challenges for this line of research.
    JEL: C11 C13 E30
    Date: 2020–08
  7. By: Li, Sheng; Wu, Feng; Guan, Zhengfei
    Keywords: Agribusiness, Research Methods/Statistical Methods, Risk and Uncertainty
    Date: 2020–07
  8. By: Marta Silva (BPLIM/BdP)
    Abstract: The Portuguese Classification of Economic Activities establishes the common categorical system to report economic activities in Portugal and suffered several revisions over time. In this presentation, I will present validarcae, a community-contributed Stata command that allows to validate the codes in a string or numerical variable reporting the economic activity according to the revision specified by the user. This tool also allows to obtain different types of aggregation for valid codes according to each revision.
    Date: 2020–08–20
  9. By: Philippe Goulet Coulombe; Maxime Leroux; Dalibor Stevanovic; Stéphane Surprenant
    Abstract: Dans ce rapport nous appliquons de nombreuses techniques d’apprentissage automatique (Machine Learning) au problème de prévision de l’activité économique au Québec et au Canada. Six groupes de modèles sont considérés : les modèles à facteurs, régressions pénalisées, régressions régularisées par sous-ensembles complets, régressions à vecteurs de support, forêts d’arbres aléatoires et les réseaux de neurones. Tous ces modèles apportent différentes façons de gérer les grands ensembles de données et de générer les formes fonc-tionnelles hautement complexes. La prédiction de 16 variables macroéconomiques québécoises et canadiennes est évaluée dans un exercice de prévision hors échantillon. Les grands ensembles de données canadiennes et américaines sont considérés. Les résultats indiquent que les méthodes machine learning, combinées avec les grands ensembles de données, ont un bon pouvoir prédictif pour plusieurs variables d’activité réelle comme le PIB, la formation brute de capital fixe et la production industrielle. Les forêts d’arbres aléatoires sont particulièrement résiliantes, suivies des réseaux de neurones. La prévision des variables du marché d’emploi est améliorée par l’utilisation des régressions pénalisées, simples ou par sous-ensembles complets. Les taux d’inflation sont prévisibles avec les forêts aléatoires et les régressions pénalisées. Quant aux mises en chantier et le taux de change USD/CAD, les méthodes machine learning n’arrivent pas à améliorer la prévision ponctuelle, mais affichent des résultats intéressants au niveau de la prévision de la direction future de ces variables.
    Keywords: , Prévision,Macroéconomie,Données massives,Machine Learning
    Date: 2020–08–27
  10. By: Mykola Babiak; Jozef Barunik
    Abstract: We study optimal dynamic portfolio choice of a long-horizon investor who uses deep learning methods to predict equity returns when forming optimal portfolios. The results show statistically and economically significant out-of-sample portfolio benefits of deep learning as measured by high certainty equivalent returns and Sharpe ratios. Return predictability via deep learning generates substantially improved portfolio performance across different subsamples, particularly the recession periods. These gains are robust to including transaction costs, short-selling and borrowing constraints.
    Date: 2020–09
  11. By: Francisco Rivadeneyra; Nellie Zhang
    Abstract: This paper presents simulation results for Canada's new large-value payments system: Lynx. We simulate the settlement process of Lynx using a large sample of payments observed in the current system (LVTS), taking the initial level of liquidity as given. We calculate the resulting liquidity usage, the payment delay and the shares of payments settled on a gross or net basis. The behaviour of participants (timing of payment submission) is assumed to remain the same as in LVTS. With an initial liquidity comparable to the collateral amount currently pledged in LVTS ($14.6 billion), Lynx FIFO Bypass would result in 28 minutes of average weighted delay and $17.3 billion of liquidity usage (the sum of intraday maximum net debit positions). Given this configuration, on average, $1.9 billion would be needed to clear non-urgent payments delayed until the end of the day, equivalent to 4.1 percent of payment value and 0.06 percent of volume. Doubling the amount of initial liquidity (to $29.3 billion) would result in 12 minutes of weighted delay. This basic configuration of Lynx requires a higher level of liquidity than LVTS and a plain-vanilla RTGS with pooled liquidity.
    Keywords: Financial services; Financial system regulation and policies; Payment clearing and settlement systems
    JEL: C5 E4 E42 E5 E58
    Date: 2020–09
  12. By: Sojung Kim; Stefan Weber
    Abstract: Uncertainty requires suitable techniques for risk assessment. Combining stochastic approximation and stochastic average approximation, we propose an efficient algorithm to compute the worst case average value at risk in the face of tail uncertainty. Dependence is modelled by the distorted mix method that flexibly assigns different copulas to different regions of multivariate distributions. We illustrate the application of our approach in the context of financial markets and cyber risk.
    Date: 2020–09
  13. By: Aliano Filho, Angelo; Melo, Teresa; Pato, Margarida Vaz
    Abstract: Motivated by a real situation arising in the Brazilian sugarcaneindustry, this paper addresses the integrated planning of harvest and transport operations over a multi-period planning horizon. The aim is to develop a schedule for the deployment of harvest and transport equipment that specifies the periods for the execution of the harvest operations on the sugarcane fields, and the type of harvesting machines and transport vehicles to be operated. These decisions are made subject to multiple constraints related to the projected crop yield, resource availability, demand for sugarcane at the mills, and further technical requirements specific to the harvest operations. The tactical plan to be determined minimizes the total cost incurred by the equipment used and the total time required to harvest all the fields. We propose a bi-objective mixed-integer non-linear programming model for this new problem. A computational study is conducted for test instances capturing the characteristics of a Brazilian milling company. Pareto-optimal solutions are identified by the Progressive Bounded Constraint Method that is extended to the problem at hand. A comparative analysis highlights the trade-offs between economic performance and harvest efficiency, thereby supporting the decision maker in making a more informed choice of the preferred tactical plan. Useful managerial insights are also provided into the profile of the harvest and transport resources that should be used under different weather conditions and work schedules.
    Keywords: Multi-objective optimization,Mixed-integer Programming,Sugarcane harvest and transport planning
    Date: 2020
  14. By: Mohammed Hichame Benbitour (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec); Evren Sahin (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec); Yves Dallery (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec)
    Abstract: We calculate optimal safety stock in a periodic review (T,S) Assemble-to-Order system having multiple components and multiple finished goods. Customer orders for finished goods arrive according to independent Poisson processes, and cannot be neither backlogged nor lost. In case of potential component stock-out, the studied system uses rush deliveries from suppliers. For this setting, approximate expressions of the optimal safety stock that minimize the sum of inventory holding and rush ordering costs are developed. Exact optimal safety stocks are calculated using discrete event simulation, and compared numerically to the approximate expressions. The model is applied to a first-tier automotive supplier and yields to a significant reduction in terms of inventory holding and rush ordering costs. A sensitivity analysis on relevant system parameters such as components demand, assembly coefficients and unit rush ordering cost is conducted.
    Keywords: inventory control,assemble-to-order,periodic review,rush orders,optimization
    Date: 2019
  15. By: Philipp Pfeiffer; Werner Roeger; Jan in ’t Veld
    Abstract: This paper uses a macroeconomic model to analyse the transmission of the COVID19-pandemic and its associated lockdown and quantify the stabilising effects of the economic policy response. Our simulations identify firm liquidity problems as crucial for shock propagation and amplification. We then quantify the effects of short-term work allowances and liquidity guarantees - central policy strategies in the European Union. The measures reduce the output loss of COVID19 and its associated lockdown by about one fourth. However, they cannot prevent a sharp but temporary decline in production.
    JEL: E32 E6 F45 J08
    Date: 2020–07
  16. By: Charles McCLEAN; ONO Yoshikuni
    Abstract: Elected officials tend to be older than most of the constituents they represent. Is this because voters generally prefer older politicians over younger ones? We investigate this question by conducting two novel survey experiments in Japan where we ask respondents to evaluate the photos of hypothetical candidates for mayor, and then alter candidate faces using artificial neural networks to make them appear as if they are younger or older, while keeping their facial structure and contours intact. Contrary to the observed candidate pool for mayors, the voters in our experiments disliked elderly candidates the most, but viewed younger candidates as equally favorable as middle-aged candidates. We also find that younger and middle-aged voters view candidates from their age group more favorably than others, whereas older voters do not, and that all voters use age as a heuristic for a candidate's issue emphases and traits. We then provide evidence for the external validity of our results using new data on actual mayoral elections. Together, these findings suggest that it is supply-side factors rather than voter demand that explain the shortage of younger politicians in public office.
    Date: 2020–08
  17. By: Magdalena Tywoniuk (Swiss Finance Institute, Students; University of Geneva - Geneva Finance Research Institute (GFRI); Swiss Finance Institute, Students)
    Abstract: Recently, for standard asset classes, the first mutual clearing agreements between Central Coun- terparties (CCPs) have come into existence. There are already global concerns over the unique threats and benefits which arise from these situations, and further concern for an extension of agree- ments to derivatives CCPs. This paper applies the current mutual agreement framework to credit default swaps (derivatives) CCPs and compares this to clearing without any such agreement. Key results concern: The magnitude of price dispersion between multiple CCPs (as trading moves asset prices away from fundamental value), the magnitude of default contagion, the price impact of pre- dation, and the disciplinary mechanism inherent in the mutual cross-margin fund (between CCPs). Current regulatory debate, concerning the safety of permitting use of the default fund to meet inter-CCP shortfalls, is settled. Finally, a large-scale dynamic simulation models the price process – through variation margin exchange – and provides real-world policy/regulatory implications for a variety of market liquidity states.
    Keywords: Mutual Agreement, Price Dispersion, Systemic Risk, CDS, Liquidation, Predation, Price Impact, Contagion, Financial Network, Over the Counter Markets
    JEL: G00 G01 G02 G14 G10 G18 G20 G23 G33
    Date: 2020–08
  18. By: Neeraj Bokde; Bo Tranberg; Gorm Bruun Andresen
    Abstract: In the Paris agreement of 2015, it was decided to reduce the CO2 emissions of the energy sector to zero by 2050 and to restrict the global mean temperature increase to 1.5 degree Celcius above the pre-industrial level. Such commitments are possible only with practically CO2-free power generation based on variable renewable technologies. Historically, the main point of criticism regarding renewable power is the variability driven by weather dependence. Power-to-X systems, which convert excess power to other stores of energy for later use, can play an important role in offsetting the variability of renewable power production. In order to do so, however, these systems have to be scheduled properly to ensure they are being powered by low-carbon technologies. In this paper, we introduce a graphical approach for scheduling power-to-X plants in the day-ahead market by minimizing carbon emissions and electricity costs. This graphical approach is simple to implement and intuitively explain to stakeholders. In a simulation study using historical prices and CO2 intensity for four different countries, we find that the price and CO2 intensity tends to decrease with increasing scheduling horizon. The effect diminishes when requiring an increasing amount of full load hours per year. Additionally, investigating the trade-off between optimizing for price or CO2 intensity shows that it is indeed a trade-off: it is not possible to obtain the lowest price and CO2 intensity at the same time.
    Date: 2020–08
  19. By: Jesús Fernández-Villaverde; Mark Koyama; Youhong Lin; Tuan-Hwee Sng
    Abstract: Patterns of political unification and fragmentation have crucial implications for comparative economic development. Diamond (1997) famously argued that “fractured land” was responsible for China's tendency toward political unification and Europe's protracted political fragmentation. We build a dynamic model with granular geographical information in terms of topographical features and the location of productive agricultural land to quantitatively gauge the effects of “fractured land” on state formation in Eurasia. We find that either topography or productive land alone is sufficient to account for China's recurring political unification and Europe's persistent political fragmentation. The existence of a core region of high land productivity in Northern China plays a central role in our simulations. We discuss how our results map into observed historical outcomes and assess how robust our findings are.
    JEL: H56 N40 P48
    Date: 2020–09
  20. By: Diao, Xinshen; Mahrt, Kristi
    Keywords: MYANMAR, BURMA, SOUTHEAST ASIA, ASIA, Coronavirus, coronavirus disease, Coronavirinae, social protection, households, income, farm income, models, remittances, poverty, rural areas, remuneration, Covid-19, Social Accounting Matrix (SAM), Myanmar Poverty and Living Conditions Survey (MPLCS), lockdown, rural households, agricultural income,
    Date: 2020
  21. By: Proaño Acosta, Christian; Lojak, Benjamin
    Abstract: In this paper we study the implementation of a state-dependent inflation target in a two-country monetary union model characterized by boundedly rational agents. In particular, we use the spread between the actual policy rate (which is constrained by the zero-lower-bound) and the Taylor rate (which can become negative) as a measure for the degree of ineffectiveness of conventional monetary policy as a stabilizing mechanism. The perception of macroeconomic risk by the agents is assumed to vary according to this measure by means of the Brock-Hommes switching mechanism. Our numerical simulations indicate a) that a state-dependent inflation target may lead to a better macroeconomic and inflation stabilization, and b) the perceived risk-sharing among the monetary union members influences the financing conditions of the member economies of the monetary union.
    Keywords: Monetary Policy,Monetary Unions,Zero Lower Bound,Inflation Targets,Behavioral Macroeconomics
    JEL: E52 F02
    Date: 2020
  22. By: Francisco J. Buera; Joseph P. Kaboski; Martí Mestieri; Daniel G. O'Connor
    Abstract: Standard dynamic models of structural transformation, without knife-edge and counterfactual parameter values, preclude balanced growth path (BGP) analysis. This paper develops a dynamic equilibrium concept for a more general class of models — an alternative to a BGP, which we coin a Stable Transformation Path (STraP). The STraP characterizes the medium-term dynamics of the economy in a turnpike sense; it is the path toward which the economy (quickly) converges from an arbitrary initial capital stock. Calibrated simulations demonstrate that the relaxed parameter values that the STraP allows have important quantitative implications for structural transformation, investment, and growth. Indeed, analyzing the dynamics along the STraP, we show that the modern dynamic model of structural transformation makes progress over the Neoclassical growth model in matching key growth and capital accumulation patterns in cross-country data, including slow convergence.
    JEL: O1 O11 O14 O4 O41
    Date: 2020–08
  23. By: Francesco Flaviano Russo (Università di Napoli Federico II and CSEF)
    Abstract: I study how to increase the capacity to test for Covid-19 with the two-swabs group testing strategy. It consists in bunching first swabs in groups and processing the second swabs individually only in case the group result is positive. Using a simulation, I derive multipliers of the lab capacity in worse case scenario that indicate how many more tests a lab can be sure to perform each day. The results show that the gains can be substantial even in case the actual fraction of positive tests is bigger than the expected fraction used to set the optimal group size.
    Keywords: Group, Test
    JEL: E1 I1 H12
    Date: 2020–09–10
  24. By: Giovanni Caggiano; Efrem Castelnuovo; Gabriela Nodari
    Abstract: This paper revisits the well-known VAR evidence on the real effects of uncertainty shocks by Bloom (Econometrica 2009(3): 623-685. doi: 10.3982/ECTA6248). We replicate the results in a narrow sense using Eviews. In a wide sense, we extend his study by working with a smooth transition-VAR framework that allows for business cycle-dependent macroeconomic responses to an uncertainty shock. We find a significantly stronger response of real activity in recessions. Counterfactual simulations point to a greater effectiveness of systematic monetary policy in stabilizing real activity in expansions.
    Keywords: uncertainty shocks, nonlinear smooth transition Vector AutoRegressions, generalized impulse response functions, systematic monetary policy
    JEL: C32 E32
    Date: 2020
  25. By: Zangari del Balzo, Gianluigi
    Abstract: In the past few days, the global scientific community has made much progress in research for the COVID-19 pandemic, but the new SARS-CoV-2 coronavirus has not yet been correctly characterized thermodynamically and much is still unknown. In particular, the current SARS-CoV-2 models lack the characterization of the virus system within its environment. This is a serious systematic error, which stands in the way of impeding research into the pandemic. In the present work, therefore, we consider the SARS-CoV-2 system with its environment, and we give a correct thermodynamic definition, through analysis and simulations, from air transport to cellular entry through the mechanism of receptor- mediated endocytosis. In studying the aerosol environment of the SARS-CoV-2 virus, we cannot omit the presence of nanoparticles or dust. Therefore, analyzing and comparing the air environments in China and Italy, we note that the Chinese and Italian regions which were at the beginning the most affected by the pandemic are also the most polluted. The same phenomenon is happening today for the United States and Brazil. We therefore propose an energy landscape theory of synergistic complexes of SARS- CoV-2 with particulate matter (PM). This could explain the optimized strategy of deep penetration of interstitial lung cells and the rapid spread of the pandemic in the most polluted areas of the planet. It could also explain the severity and difficulty of treating the forms of interstitial pneumonia occurred in Italy and worldwide. The energy landscape theory of complexes of SARS-CoV-2 with particulate matter (PM), leads to crucial methodological constraints aimed at containing systematic errors in experimental laboratory procedures and in mathematical modeling, which can allow and accelerate the definition of the mechanism of action of the virus and therefore the realization of the appropriate therapies and health protocols.
    Date: 2020–03–20
  26. By: Hess Chung; Brian M. Doyle; James Hebden; Michael Siemer
    Abstract: We consider three ways that a monetary policy framework may employ a range for inflation outcomes: (1) ranges that acknowledge uncertainty about inflation outcomes (uncertainty ranges), (2) ranges that define the scope for intentional deviations of inflation from its target (operational ranges), and (3) ranges over which monetary policy will not react to inflation deviations (indifference ranges). After defining these three ranges, we highlight a number of costs and benefits associated with each. Our discussion of the indifference range is accompanied by simulations from the FRB/US model, illustrating the potential for long-term inflation expectations to drift within the range.
    Keywords: Forward guidance; Monetary policy
    JEL: E31 E52 E58
    Date: 2020–08–27
  27. By: Taro Ohno (Associate Professor, Research Center for Social Systems, Shinshu University); Junpei Sakamaki (Researcher, Policy Research Institute, Ministry of Finance); Daizo Kojima (Associate Professor, Graduate School of Agricultural and Life Sciences, The University of Tokyo)
    Abstract: Following generous tax deductions, Japan's income tax base is facing shrinkage. However, this trend has evolved not only due to changes to the system, but also due to changes to the income distribution and population composition. In this study we use household micro data from the National Survey of Family Income and Expenditure (NSFIE, 1994-2014) to explicate the state of deductions and trends in household distribution over a 20-year period while considering each factor fs contribution to changes in the tax base, through their decomposition. Using a micro-simulation analysis, we also assess the effects of recent changes to the tax system on the tax base. Based on a long-term perspective, while the tax base has been eroded mainly due to the effects of falling incomes and an aging population, the contribution of system changes in response to such pressures has been limited. The inclusion of both the expansion and contraction periods in the deduction system also has an effect. Based on a short-term perspective, changes to the system have had a certain impact because, particularly in the 2000s, the tax base was expanded by reducing deductions. However, this effect has eventually been offset by the changes in income distribution and population composition. Following the ongoing effects of change such as falling incomes and population aging, it is necessary to fundamentally reform the income tax system so that it can have a greater effect, including restoring its fiscal funding and income redistribution functions, as well as the ideal form of the tax base.
    Keywords: Income tax, tax deduction, tax base, National Survey of Family Income and Expenditure
    JEL: C15 H24
    Date: 2020–08
  28. By: Jeehoon Han; Bruce D. Meyer; James X. Sullivan
    Abstract: This paper addresses the economic impact of the COVID-19 pandemic by providing timely and accurate information on the impact of the current pandemic on income and poverty to inform the targeting of resources to those most affected and assess the success of current efforts. We construct new measures of the income distribution and poverty with a lag of only a few weeks using high frequency data from the Basic Monthly Current Population Survey (CPS), which collects income information for a large, representative sample of U.S. families. Because the family income data for this project are rarely used, we validate this timely measure of income by comparing historical estimates that rely on these data to estimates from data on income and consumption that have been used much more broadly. Our results indicate that at the start of the pandemic, government policy effectively countered its effects on incomes, leading poverty to fall and low percentiles of income to rise across a range of demographic groups and geographies. Simulations that rely on the detailed CPS data and that closely match total government payments made show that the entire decline in poverty that we find can be accounted for by the rise in government assistance, including unemployment insurance benefits and the Economic Impact Payments. Our simulations further indicate that of those losing employment the vast majority received unemployment insurance, though this was less true early on in the pandemic and receipt was uneven across the states, with some states not reaching a large share of their out of work residents.
    JEL: H53 I32 J65
    Date: 2020–08

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