Hasil untuk "Economic history and conditions"

E. Bonacich

Florian Gerth, Martin O’Brien, Karol S. Sikora

This study investigates the empirical interaction between changing socioeconomic challenges and the construction sector in Cambodia. The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. We find that the link between economic development and activity in construction is more complex than previously believed, with the role of the construction industry changing during economic development. Results show that the number of private dwelling construction projects can be explained by the ratio of primary education (-3.4), number of people employed in the educational sector (13.6), road construction (0.8), and net exports (-0.5). Future research should focus on i) potential endogeneity issues. This might emerge because activity might be conditional on the state of construction which, on the other hand, drives overall activity. ii) disentangling the effects of developments within domestic financial markets and their role in efficiently allocating financial capital to the real economy. Lastly, the significant impact of the Covid-19 crisis on the Cambodian economy, particularly the role of FP (fiscal policy) and MP (monetary policy) and efficient resource allocation within the construction industry. This aspect is crucial, as different industries responded variably to the shock and lock-down caused by Covid-19.

Horst Treiblmaier

Dee Hock, the founder of Visa, coined the term 'chaordic' to describe simultaneously chaotic and ordered systems. Based on his reasoning, we introduce the Theory of Chaordic Economics to explain how economic systems are transformed by two disruptive technologies: namely Artificial Intelligence and Blockchain. Artificial intelligence can generate novel output through algorithmic yet rather unpredictable processes. Blockchain creates deterministic results without central authorities and relies on elaborated protocols that prescribe how consensus can be reached within a network of peers. The amalgamation of chaos and order produces chaordic economic systems and can yield hitherto unthinkable economic structures.

Craig S Wright

This paper presents a praxeological analysis of artificial intelligence and algorithmic governance, challenging assumptions about the capacity of machine systems to sustain economic and epistemic order. Drawing on Misesian a priori reasoning and Austrian theories of entrepreneurship, we argue that AI systems are incapable of performing the core functions of economic coordination: interpreting ends, discovering means, and communicating subjective value through prices. Where neoclassical and behavioural models treat decisions as optimisation under constraint, we frame them as purposive actions under uncertainty. We critique dominant ethical AI frameworks such as Fairness, Accountability, and Transparency (FAT) as extensions of constructivist rationalism, which conflict with a liberal order grounded in voluntary action and property rights. Attempts to encode moral reasoning in algorithms reflect a misunderstanding of ethics and economics. However complex, AI systems cannot originate norms, interpret institutions, or bear responsibility. They remain opaque, misaligned, and inert. Using the concept of epistemic scarcity, we explore how information abundance degrades truth discernment, enabling both entrepreneurial insight and soft totalitarianism. Our analysis ends with a civilisational claim: the debate over AI concerns the future of human autonomy, institutional evolution, and reasoned choice. The Austrian tradition, focused on action, subjectivity, and spontaneous order, offers the only coherent alternative to rising computational social control.

Neeraj Pandey, Abhineet Agarwal, Raju Roychowdhury et al.

Analysis of the urban population fraction data for sixteen populous countries over the last fifty years reveals a universal increase in urbanization, exhibiting four qualitatively distinct temporal patterns: (i) continuously accelerating growth, (ii) continuously decelerating growth, (iii) two-phase growth transitioning from acceleration to deceleration, and (iv) two-phase growth transitioning from deceleration to acceleration. To understand the origin of these diverse urbanization trajectories, we develop a simple coarse-grained model in which a country is segregated into two regions, a rural and an urban region. Population in each region evolves due to natural (sexual) growth and migration from rural to urban areas, with the migration rate governed by economic inequality, quantified through the difference in GDP per capita between the two regions. The GDP per capita of both regions is assumed to grow exponentially with distinct rates. We demonstrate that this minimal model, involving four dynamical variables and a small number of demographic and economic parameters, is capable of reproducing all four empirically observed urbanization patterns. Assuming demographic and economic parameters remain approximately constant over a 50-year timescale, we estimate coarse-grained parameters for the United States using empirical data and obtain optimized values that accurately reproduce its observed urbanization trajectory. Our results highlight how simple demographic-economic interactions can generate rich and diverse urbanization dynamics.

Marco Pangallo, R. Maria del Rio-Chanona

Economic agent-based models (ABMs) are becoming more and more data-driven, establishing themselves as increasingly valuable tools for economic research and policymaking. We propose to classify the extent to which an ABM is data-driven based on whether agent-level quantities are initialized from real-world micro-data and whether the ABM's dynamics track empirical time series. This paper discusses how making ABMs data-driven helps overcome limitations of traditional ABMs and makes ABMs a stronger alternative to equilibrium models. We review state-of-the-art methods in parameter calibration, initialization, and data assimilation, and then present successful applications that have generated new scientific knowledge and informed policy decisions. This paper serves as a manifesto for data-driven ABMs, introducing a definition and classification and outlining the state of the field, and as a guide for those new to the field.

Konrad Turkowski, Krzysztof Kupren, Waldemar Kozłowski

The state, development directions, opportunities and ways to improve inland fisheries management in Poland are described and discussed. Most of the country's inland waters are public. For fishing purposes, they are divided into fisheries districts. With exceptions, users of the fishing districts are selected through competitions. The user is obliged to conduct rational fisheries management in accordance with a fisheries management plan. Attention is drawn to the overdeveloped national fisheries administration and the possibilities for improvement. The fish stocks in the fishing districts are exploited by both a small group of commercial fishermen and a large group of anglers. While the information covering the basic data on harvest, stocking and other treatments in commercial fisheries can be considered sufficient, the lack of information about the number and catches of anglers is the greatest obstacle to the implementation of rational fisheries management. The preparation of a universal and mandatory system for acquiring angling data should be a priority for the national water administration, representing the owner of public inland waters in Poland.  

S. Wood, A. Jina, Meha Jain et al.

Abstract A long history of household-level research has provided important local-level insights into climate adaptation strategies in the agricultural sector. It remains unclear to what extent these strategies are generalizable or vary across regions. In this study we ask about three potential key factors influencing farming households’ ability to adapt: access to weather information, household and agricultural production-related assets, and participation in local social institutions. We use a 12-country data set from sub-Saharan Africa and South Asia to explore the links between these three potential drivers of agricultural change and the likelihood that farmers made farm-associated changes, such as adopting improved crop varieties, increasing fertilizer use, investing in improved land management practices, and changing the timing of agricultural activities. We find evidence that access to weather information, assets, and participation in social institutions are associated with households that have reported making farming changes in recent years, although these results vary across countries and types of practices. Understanding these drivers and outcomes of farm-associated changes across different socio-economic and environmental conditions is critical for ongoing dialogues for climate-resilient strategies and policies for increasing the adaptive capacity of smallholders under climate change.

Mario D. Tello

In a decade of low TFP —factorial total productivity— in Latin America, the paper shows evidence of the low level of TFP due to the degree of technical inefficiency of companies in the Peruvian productive sector case. For this, the technical efficiency indices of 116 875 companies (83 271 formal and 33 604 informal) distributed in 25 regions and ten productive sectors (agriculture, livestock, agriculture, mining, fishing, manufacturing, construction, commerce, hotels and restaurants, and the rest are non-governmental services). The estimates yielded a general average efficiency index for the regions and sectors of Peru of 37.94 —in other words, the total product of the companies would multiply by 2.6 without requiring additional productive factors—. This figure suggests that government or company interventions that induce technically efficient behaviors in production can contribute to increasing the TFP of the economy, probably at lower cost and time.

Michael Gref, Nike Matthiesen, Christoph Schmidt et al.

Automatic speech recognition systems have accomplished remarkable improvements in transcription accuracy in recent years. On some domains, models now achieve near-human performance. However, transcription performance on oral history has not yet reached human accuracy. In the present work, we investigate how large this gap between human and machine transcription still is. For this purpose, we analyze and compare transcriptions of three humans on a new oral history data set. We estimate a human word error rate of 8.7% for recent German oral history interviews with clean acoustic conditions. For comparison with recent machine transcription accuracy, we present experiments on the adaptation of an acoustic model achieving near-human performance on broadcast speech. We investigate the influence of different adaptation data on robustness and generalization for clean and noisy oral history interviews. We optimize our acoustic models by 5 to 8% relative for this task and achieve 23.9% WER on noisy and 15.6% word error rate on clean oral history interviews.

Hayato Kato, Hirofumi Okoshi

Do low corporate taxes always favor multinational production over economic integration? We propose a two-country model in which multinationals choose the locations of production plants and foreign distribution affiliates and shift profits between them through transfer prices. With high trade costs, plants are concentrated in the low-tax country; surprisingly, this pattern reverses with low trade costs. Indeed, economic integration has a non-monotonic impact: falling trade costs first decrease and then increase the plant share in the high-tax country, which we empirically confirm. Moreover, allowing for transfer pricing makes tax competition tougher and international coordination on transfer-pricing regulation can be beneficial.

Jorge Guillermo Osorio Vaccaro

Desde la aparición de la Hipótesis de Expectativas Racionales introducida en la macroeconomía a fines de los años 70 y hasta fines del siglo XX, las tensiones y desacuerdos entre la mayoría de los economistas fueron notables, así como las fuertes críticas, referentes a la futilidad o poco significado de las teorías que se plantearon. Sin embargo, parece haberse avanzado hacia una convergencia en la forma de conceptualizar la macroeconomía y esto ha sucedido porque los hechos del mundo real no pueden ser ignorados. Las creencias compartidas por la mayoría de economistas ortodoxos, han dado lugar a lo que hoy es la forma de considerar la ciencia económica desde la perspectiva de la llamada Macroeconomía Nueva Keynesiana y su extensión el Nuevo Consenso en Macroeconomía, que parece tener criterios unificados y ha permitido una convergencia útil. La clave para dicha convergencia estaría en aceptar, entre otras cosas, la existencia de rigideces tanto en los precios como en los salarios nominales, que la demanda y la oferta agregadas son importantes para regular la actividad económica, que hay competencia imperfecta en el mercado de bienes y que la política económica debe privilegiar el uso de la política monetaria, la misma que debe orientarse fundamentalmente a controlar la inflación. Sin embargo, una importante corriente de pensamiento económico, el Poskeynesianismo, no está de acuerdo con muchos de los enfoques de los economistas del Nuevo Consenso y ha planteado críticas que merecerían consideración. De hecho, no todos los economistas han convergido o lo están haciendo, ya que existen diferencias importantes entre la ortodoxia basada en el enfoque Nuevo Keynesiano y la heterodoxia Poskeynesiana.

Zoe Goss, Daniel Coles, Matthew Piggott

This tidal stream energy industry has to date been comprised of small demonstrator projects made up of one to a four turbines. However, there are currently plans to expand to commercially sized projects with tens of turbines or more. As the industry moves to large-scale arrays for the first time, there has been a push to develop tools to optimise the array design and help bring down the costs. This review investigates different methods of modelling the economic performance of tidal-stream arrays, for use within these optimisation tools. The different cost reduction pathways are discussed from costs falling as the global installed capacity increases, due to greater experience, improved power curves through larger-diameter higher-rated turbines, to economic efficiencies that can be found by moving to large-scale arrays. A literature review is conducted to establish the most appropriate input values for use in economic models. This includes finding a best case, worst case and typical values for costs and other related parameters. The information collated in this review can provide a useful steering for the many optimisation tools that have been developed, especially when cost information is commercially sensitive and a realistic parameter range is difficult to obtain.

Pavel Čoupek

For a prime $p>2$ and a smooth proper $p$-adic formal scheme $X$ over $\mathcal{O}_K$ where $K$ is a $p$-adic field, we study a series of conditions ($\mathrm{Cr}_s$), $s\geq 0$ that partially control the $G_K$-action on the image of the associated Breuil-Kisin prismatic cohomology $\mathrm{R}Γ_Δ(X/\mathfrak{S})$ inside the $A_{\mathrm{inf}}$-prismatic cohomology $\mathrm{R}Γ_Δ(X_{A_{\mathrm{inf}}}/A_{\mathrm{inf}})$. The condition ($\mathrm{Cr}_0$) is a criterion for a Breuil-Kisin-Fargues $G_K$-module to induce a crystalline representation used by Gee and Liu, and thus leads to a proof of crystallinity of $\mathrm{H}^i_{\text{ét}}(X_{\overlineη}, \mathbb{Q}_p)$ that avoids the crystalline comparison. The higher conditions ($\mathrm{Cr}_s$) are used to adapt the strategy of Caruso and Liu in order to establish ramification bounds for the mod $p$ representations $\mathrm{H}^{i}_{\text{ét}}(X_{\overlineη}, \mathbb{Z}/p\mathbb{Z}),$ for arbitrary $e$ and $i$, which extend or improve existing bounds in various situations.

Rene Carmona

This is an expanded version of the lecture given at the AMS Short Course on Mean Field Games, on January 13, 2020 in Denver CO. The assignment was to discuss applications of Mean Field Games in finance and economics. I need to admit upfront that several of the examples reviewed in this chapter were already discussed in book form. Still, they are here accompanied with discussions of, and references to, works which appeared over the last three years. Moreover, several completely new sections are added to show how recent developments in financial engineering and economics can benefit from being viewed through the lens of the Mean Field Game paradigm. The new financial engineering applications deal with bitcoin mining and the energy markets, while the new economic applications concern models offering a smooth transition between macro-economics and finance, and contract theory.

Kexin Chen, Chi Seng Pun, Hoi Ying Wong

Social distancing has been the only effective way to contain the spread of an infectious disease prior to the availability of the pharmaceutical treatment. It can lower the infection rate of the disease at the economic cost. A pandemic crisis like COVID-19, however, has posed a dilemma to the policymakers since a long-term restrictive social distancing or even lockdown will keep economic cost rising. This paper investigates an efficient social distancing policy to manage the integrated risk from economic health and public health issues for COVID-19 using a stochastic epidemic modeling with mobility controls. The social distancing is to restrict the community mobility, which was recently accessible with big data analytics. This paper takes advantage of the community mobility data to model the COVID-19 processes and infer the COVID-19 driven economic values from major market index price, which allow us to formulate the search of the efficient social distancing policy as a stochastic control problem. We propose to solve the problem with a deep-learning approach. By applying our framework to the US data, we empirically examine the efficiency of the US social distancing policy and offer recommendations generated from the algorithm.

Zachary Feinstein

In this paper, we study the financial and economic implications of a zombie epidemic on a major industrialized nation. We begin with a consideration of the epidemiological modeling of the zombie contagion. The emphasis of this work is on the computation of direct and indirect financial consequences of this contagion of the walking dead. A moderate zombie outbreak leaving 1 million people dead in a major industrialized nation could result in GDP losses of 23.44% over the subsequent year and a drop in financial market of 29.30%. We conclude by recommending policy actions necessary to prevent this potential economic collapse.

S. Witter, H. Wurie, Pamela Chandiwana et al.

Sylwia Michalska, Anna Rosa, Trần Thị Minh Thi

David Fée

This article explores the links between housing, housing policy and well-being in England essentially, as well as the UK in a more limited way. It focuses on three central points : first, it explains how assessing subjective well-being has become an official concern in relation to housing in response to government demands. It builds on a long-standing tradition of assessing objective or material well-being in the field of housing. Second, in a historical perspective, this article focuses on the changing official discourse in relation to housing to underscore how material well-being has been construed over time. Lastly, the article analyses post-2010 housing measures and posits that there is a discrepancy between the official rhetoric of well-being and the policies implemented since 2010.