Aggregate Economy Research Articles

Interregional Demand for Workers and the Effects of Labor Income Taxation

We study the short-run impacts of labor income taxation in an aggregate economy of N>2 regions. The distinct regions demand workers. Each region is endowed with one unit of immobile capital. The aggregate economy also has one unit of labor that is mobile across the regions. All regions produce a final good with identical Cobb-Douglas production functions. The price of output is normalized to unity. We perform five tasks. First, we focus on the benchmark case in which no region taxes either capital or labor. We find the equilibrium wage, the allocation of workers across the regions, and the total income of labor and capital. Second, we study the impact of a tax τ on labor income in region 1 when the other N-1 regions do not tax labor income. We ascertain the after-tax return to labor in region 1, the equilibrium wage, and the allocation of labor across the regions. Third, we compute the total income of capital and labor and the tax revenue in region 1. Fourth, we discuss whether workers in region 1 are better off with a tax on labor income. Finally, we comment on the policy implications of our research.

Violence, Institutional Shocks and Development

The wars of 1792-1815 constituted the last and biggest military conflict in pre-modern Europe. This essay reviews the available evidence concerning their economic impact on the German lands. Given the low level of fiscal development there, taxes and capital markets were of limited relevance for the mobilization of resources for war-related purposes relative to requisitions and exactions on the spot. Adverse effects of the wars on the aggregate economy in the short run were limited, and post-war reconstruction was achieved within a half-decade. The 1810s also saw the transition from a Malthusian disequilibrium to a post-Malthusian regime, which raises the question of whether the wars produced institutional shocks favouring economic development in the long run. The available evidence supports the view that links the increase of the state size, which resulted from the wars, with Smithian growth.

Aggregate and Intergenerational Implications of School Closures: A Quantitative Assessment

A majority of governments around the world unprecedentedly closed schools in response to the COVID-19 pandemic. This paper quantitatively investigates the macroeconomic and distributional consequences of school closures through intergenerational channels in the medium-and long-term. The model economy is a dynastic overlapping generations general equilibrium model in which schools, in the form of public education investments, complement parental investments in producing children’s human capital. We calibrate the stationary equilibrium of the model to the U.S. economy and compute the equilibrium responses following unexpected school closure shocks. We find that school closures have moderate long-lasting adverse effects on macroeconomic aggregates such as output. The accumulated output loss over the next century relative to the annual output, following a half-year-long closure, exceeds 5%. In addition, we find that school closures reduce intergenerational mobility, especially among older children. Finally, we find that lower substitutability between public and parental investments induces larger damages in the aggregate economy and overall lifetime incomes of the affected children while mitigating negative impacts on intergenerational mobility. In all findings, heterogeneous parental responses to school closures play a key role. Our results provide a quantitatively relevant dimension to consider for policymakers assessing potential costs of school closures.

Using artificial neural networks to forecast producer price index for New Zealand

Trend in the producer price is of much value to the central bank authorities in identifying the cost-push inflation that can improve their understanding of future directions of inflation in the aggregate economy and informulating sound policies and macroeconomic plans. Forecasting of the producer price movement is complex; the popular use of conventional methods is fraught with inaccuracies which often produces misleading results. This study explored the reliability and accuracy of the use of artificial neural networks (ANNs) for modelling and predicting producer price index (PPI) trend in New Zealand. The study also compared ANNs results with those produced by the autoregressive integrated moving average (ARIMA) as an alternative. Results showed that the ANNs model outperformed the ARIMA model as a more reliable and accurate tool for time series data prediction. The method developed could guide economists and macroeconomic policymakers in making more accurate forecasts.

Dynamic Models of the Creative Industries’ Behaviour

The aim of the paper is to analyse the models describing the development of the Creative Industries in Slovakia. Creative industries are described as the industrial components of the economy in which creativity is an input and content or intellectual property is the output. The creative industries have therefore appeared to be newly represented as a significant and rapidly growing set of industries; an important sector, in other words, for policy consideration. Based on the following findings, we can conclude that the second model is precisely predicting the relationship between the growth in the creative industries and in the aggregate economy in Slovakia. With improved cultural statistics, also a more developed and theoretically better founded analysis would be possible. We therefore see our article primarily as a much-needed step towards developing statistical tools in empirical cultural policy on a consistent basis.

Wealth Management Ability,Relational Capital and Operational Performance——An Empirical Study on Chinese Commercial Banks

With the continuous rise of China's economic aggregate and the annual growth of national income, wealth management services of commercial banks have developed rapidly. By using annual data of 61 commercial banks in China from 2014 to 2018, this study employs the panel data model to analyze the influence of wealth management ability of commercial banks on business performance from the perspective of relational capital. The empirical results show that there are different effects of wealth management ability and relational capital on operational performance. First, issuing ability of wealth management has a negative impact on business performance, but it is not statistically significant. Its interaction with relational capital has a significant and positive effect on business performance. Second, risk control ability of wealth management has a significant and positive effect on business performance, whereas its interaction with relational capital has a significant and negative impact on business performance. Third, the richness of wealth management products has a significantly positive effect on business performance. And the interaction with relational capital also has a significantly positive effect on business performance. Finally, the normative ability of information disclosure has a significantly negative impact on business performance. However, its interaction with relational capital has a positive effect on business performance, but it is not statistically significant.

Экономическая динамика при неоднородном адаптивном обучении: условия стабильности в терминах агрегированной экономики

We provide sufficient conditions for stability of a linear structurally heterogeneous economy under heterogeneous learning of agents, extending the results of Honkapohja and Mitra (2006), Kolyuzhnov (2011), and Bogomolova and Kolyuzhnov (2019). Sufficient conditions for stability under heterogeneous mixed RLS/SG learning for four classes of models: models without lags and with lags of the endogenous variable and with t or t-1- dating of expectations, are provided for the cases of the diagonal structure of the shock process behaviour or the heterogeneous RLS learning and are presented in terms of structural heterogeneity and are independent of heterogeneity in learning. The results are based on the negative diagonal dominance approach and are provided, first, in terms of the existence of the weights for aggregation of endogenous variables and of expectations across agents, interrelated in a special way, and then in terms of the E-stability of a suitably defined aggregate economy. The fundamental nature of the approach adopted in the paper allows one to apply its results to a vast majority of the existing and prospective linear and linearized economic models (including estimated DSGE models) with adaptive learning of agents.

Learning and Money Adoption

Hirshleifer (1971) famously argued that the public disclosure of socially useless information hurts welfare because it creates unwanted economic fluctuations. We show that this logic can fail if the disclosed information concerns the medium of exchange. We consider an economy where agents gradually learn about the quality of a new asset and coordinate to adopt it as a medium of exchange or abandon it. The demand of this money-like asset can be partially convex, and the convexity translates more economic fluctuations into higher asset prices, making the asset a more useful payment device. Therefore more information disclosure sometimes raises welfare, even when information is not socially useful, i.e. when new information does not affect agents’ adoption decisions. When there are competing monies, the aggregate liquidity and welfare can be non-monotone in beliefs and hence a good news about a new money can be a bad news for the aggregate economy. In an extension with heterogenous agents we illustrate that the presence of some hodlers can change the allocation substantially.

The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data

The current knowledge system of macroeconomics is built on interactions among a small number of variables, since traditional macroeconomic models can mostly handle a handful of inputs. Recent work using big data suggests that a much larger number of variables are active in driving the dynamics of the aggregate economy. In this paper, we introduce a knowledge graph (KG) that consists of not only linkages between traditional economic variables but also new alternative big data variables. We extract these new variables and the linkages by applying advanced natural language processing (NLP) tools on the massive textual data of academic literature and research reports. As an example of potential applications, we use it as the prior knowledge to select variables for economic forecasting models in macroeconomics. Compared to statistical variable selection methods, KG-based methods achieve significantly higher forecasting accuracy, especially for long run forecasts.

Using financial accounts: A central banking perspective

The development of financial accounts is high on the global policy agenda. These accounts have become an essential element of the SNA, drawing from the traditional description of real economic aggregates augmented to present information on financial flows and positions. Several steps have been taken in recent years to refine important aspects of this framework, with the goal of building “integrated sectoral financial accounts”. To this end, two areas of focus are important. One relates to collecting the statistics to “fill” standard economic accounts. Large data collections have been undertaken since the 2007–09 Great Financial Crisis to build better-quality, more comprehensive and flexible data sets. A second important issue is to highlight how these statistics can be useful and support public policy. These areas are of particular relevance for central banks. As producers, they have been highly involved in the statistical exercises launched to address the challenges highlighted by the 2007-09 crisis. As data users, they have an increasing demand for information in order to understand, and act on, the financial system in pursuing monetary and financial stability policy objectives; financial accounts represent a key opportunity to address these information needs.

Temporal and spatial variations of impervious surface landscape pattern and the driving factors in Xiamen City, China

Xiamen is one of China's five major special economic zones and is the core city of Haixi Economic Zone, with a high level of urbanization. Monitoring and driving force analysis of impervious surfaces can increase our understanding of urbanization process and have important significance for urban landscape pattern research and urban ecological environment construction. We used the Landsat remote sensing image data from 1978 to 2018 to reveal the temporal and spatial variation characteristics of the impervious surface landscape in Xiamen in the past 40 years, using the full-restricted least squares method, landscape pattern analysis, slope gradient analysis and correlation analysis. We further analyzed its relationship with social and economic factors. The results showed that, during 1978-2018, the impervious surface of Xiamen increased by 348.96 km2, with a mean annual increase of 8.72 km2. The impervious surface dynamics reached a maximum of 9.0% in 2005-2010. More than 86.6% of the impervious surface of Xiamen was distributed within 6° of slope, with a tendency to expand to a greater slope in 2010-2018. With the increases of slope, the proportion of impervious surface decreased, the density of plaque decreased with the shape tending to be regular and continuous, the degree of fragmentation of the impervious surface increased. The increases of impervious surface in Xiamen was significantly related to the regional economic aggregate and population. In the study period, the spatial pattern of impervious surface in Xiamen significantly altered. In the future urban planning process, the extent and speed of impervious surface expansion should be coordinated to avoid ecological problems caused by excessive impervious surface to meet the need for sustainable development of Xiamen.

Methodological problems in the economic measurement of tourism: the need for new sources of information

Tourism alone does not comprise an economic sector. Tourism activities are found in the agriculture, industry, and service sectors. As a result, tourism can contribute considerably to the growth of a country’s economy. Currently, all tourism activities are included in the GDP, but policymakers and entrepreneurs need to identify tourism’s contribution to the overall economy. However, the available statistics are not always homogeneous across countries, nor are they collected in a timely manner. The geographic details of available statistics are also insufficient. Estimating the value tourism adds to the economy is methodologically complex because of varying operational definitions and the use of different statistical sources. Conversely, the production of business registers offers a new opportunity to estimate economic aggregates and, in particular, the value added of the tourism sector, even at the local level. Nevertheless, some methodological problems remain.

The impact of the Triple Helix model on the local development of Western Poland

Purpose: The aim of this paper is to show the positive impact of public support for the relationships within the triple helix model on the local development of Western Poland (WP). Design/methodology/approach: The paper presents the econometric model based on backward stepwise multiple regression in which the explanatory variables were expenses aggregated into 44 categories dedicated to triple helix model. The model defines a theoretical framework for local innovation systems in 111 counties of WP (5 western voivodeships). An economic aggregate based on average salaries was chosen as a dependent variable, treated as a measure of local development. Findings: Relationships diagnosed within triple helix model were supported by public expenditures from the European Union cohesion policy in 2007-2013. Two hypotheses were proposed in the paper. In the first one, a presumption was expressed for the positive impact of statistically significant expenditures on innovative activity, and technical and knowledge infrastructure for the local development of WP. The hypothesis was tested in basic and extended variants. In the second one, a presumption was expressed in which public expenditures on technical infrastructure were more influential for the local development of WP than expenditures on knowledge infrastructure. The first hypothesis was confirmed in both basic and extended variants. The second hypothesis could not be confirmed as a result of the research procedure. Importantly, bi-lateral synergy effects in the triple helix model within the researched counties of WP, positively influencing local development, are evident. Research limitations/implications: The Triple helix model, treated as a template for creating local innovation systems, could be extended into quadruple helix model. Future research may include variables related to “society” as forth side supporting innovative processes in local economy. Practical implications: The results of the regression model confirm the positive impact of expenses related to the broadly understood innovation activities on local development. In contrast, expenditure on technical infrastructure, representing the administration–business relationship, demonstrates a negative impact on the adopted local development measures. Originality/value: the paper presents the methodology, that could be used in diagnosing trilateral relationships occurring at the interface of science–business–administration. In the research, only bilateral relations have been diagnosed at the interface of science–business and administration–science.

Digital Cubic Space as a New Economic Augmented Reality

Introduction. Digital cubic space implies the formation of new economic augmented reality into socio-economic life at various levels of economic aggregation, thus accelerating the digitalization of Ukrainian economy. Problem Statement. Taking into account the existing R&D developments in the field of knowledge of digital economy, not yet learned is transformation of digital technologies at the enterprise, based on the introduction of innovative changes such as BlockChain, FinTech, front office, back office, middle office, omni-business. Purpose. Disclosure of the content of digital cubic space as a new economic complemented reality and presentation of its characteristics through the knowledge of qualitative functioning of FinTech’s and the peculiarities of BlockChain, the formation of which occurs during the digitization of the economy, for the purpose of creation of digital products/services. Materials and methods. Based on the dialectic, system and matrix methods, digital cubic space becoming a new supplemented reality during the digitization of Ukrainian economy has been studied. A comparison of innovative development ratings that affects the speed of digitalization in individual countries around the world has been used. Results. By analogy with the construction of well-known Rubik’s cube, author’s proved that the formation of an efficiently functioning digital economy is possible in conditions of simultaneous harmonic relations “science-business-government-education” resulting in a special environment — digital cubic space of new economic augmented reality. The FinTech 1.0, FinTech 2.0, FinTech 3.0, FinTech 3.5 technologies have been distinguished. The author’s interpretation of the content of digital economy and the category “digital cubic space” has been proposed. The distinction between virtual, extended, expanded, improved, enriched, mixed realities is indicated. Conclusions. Digital cubic space forms a new economic augmented reality at the expense of digital discoveries, the volume of the market of digital products/services. Such institutions are included in the driving forces of digital cubic space: digital hubs, digital platforms, digital currency, FinTech, RegTech, SupTech, new industrial technology Industry 4.0.

Nowcasting global trade in goods and services

World economic aggregates are compiled infrequently and released after considerable lags. There are, however, many potentially relevant series released in a timely manner and at a higher frequency that could provide significant information about the evolution of global aggregates. The challenge is then to extract the relevant information from this multitude of indicators and combine it to track the real-time evolution of the target variables. We develop a methodology based on dynamic factor models adapted for variables with heterogeneous frequencies, ragged ends and missing data. We apply this methodology to nowcast global trade in goods in goods and services. In addition to monitoring these variables in real time, this method can also be used to obtain short-term forecasts based on the most up-to-date values of the underlying indicators.

Bank Geographic Diversification and Systemic Risk

Abstract Exploiting staggered interstate banking deregulation as exogenous shocks to bank geographic expansion, we examine the causal effect of geographic diversification on systemic risk. Using the gravity-deregulation approach, we find that bank geographic diversification leads to higher systemic risk measured by the change in conditional value at risk ($\Delta$CoVaR) and financial integration (Logistic($R^{2}))$. Furthermore, we document that geographic diversification affects systemic risk via its impact on asset similarity. The impact of geographic diversification on systemic risk is stronger in BHCs located in states comoving less with the U.S. aggregate economy.

Observing and Shaping the Market: The Dilemma of Central Banks

While the central bank observes the market activity to assess economic fundamentals, it shapes the market outcome through its policy interventions. The more the central bank influences the market, the more it spoils the informational content of economic aggregates. How should the central bank act and communicate when it derives its information from observing the market? This paper analyses the optimal central bank’s action and disclosure under endogenous central bank’s information for three operational frameworks: pure communication, action and communication, and signaling action. When the central bank takes an action, it would be optimal for the central bank to be fully opaque to prevent its disclosure from deteriorating the information quality of market outcomes. However, in the realistic case where central bank’s action is observable, it may be optimal to refrain from implementing any action.

Financialization and the Labor Share of Income

Abstract Financialization has been growing importance in macroeconomic perspectives since the finance-dominated capitalist relations have captured many of the specific positions in an aggregate economy. However, the empirical literature has substantially ignored the examination of the link between an increasing scale of financialization and the rising income inequality. In this study, a major hypothesis is based on the fact that the finance-dominated capitalism has a considerable effect on distributional practices through the channels of bargaining power. By applying the Kaleckian approach, the paper investigates the relationship between financialization and the labor share of national income using a panel dataset of 52 countries over the 1992-2012 period. The results suggest that a higher level of stock market development leads to a more unequal distribution of income and, thus, to the decline of wage share in the national income. Other factors such as globalization and technical change can also exacerbate the decline of wages, coupled with a decrease in the bargaining position of labor measured by unemployment rate and labor force participation rate.

Macrologistics instrumentation: Integrated national freight-flow and logistics cost measurement

The objective of this research is to aid macrologistics decision-making through the development and interpretation of national freight-flow and logistics cost measurements, i.e. macrologistics instrumentation. This provides the systemic view of the national freight logistics landscape that is required to address logistics challenges within the context of a country's socio-economic objectives. The results highlight that South Africa's macrologistics costs exceed that of trading partners, with road transport the dominant cost contributor. Investing in domestic intermodal solutions will reduce both transport and externality costs. This, in turn, will improve the competitiveness of domestic and international freight, and support economic and ecological development objectives. Rail branch line densification will improve market access for rural economies and reduce logistics costs while supporting social development objectives. These applications provide examples of data-driven policy development and infrastructure investments. The level of spatial and sectoral disaggregation in the South Africa's Freight Demand ModelTM, and the flow-level link with a logistics costs model, within the context of the national input-output model, is to the best of our knowledge unique. This link to economic aggregates in the South Africa's Freight Demand ModelTM input data bridges logistics' analytical gap to macroeconomic decision-making.

A Bayesian evaluation of an efficiency-wage model with indeterminacy

ABSTRACTThis paper provides a quantitative assessment of a general equilibrium economy with non-Walrasian labour markets. Indeterminacy in the economy does not require production externalities or increasing returns but it rests on replacing the labour supply curve by a no-shirking condition on the efficiency-wage labour markets. The model is estimated on U.S. data via full information Bayesian methods. The shirking model is capable of matching several stylized facts of the aggregate economy and the labour market. Data favour a version of the artificial economy that is characterized by determinacy.