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This paper aims to explain the main empirical facts of housing markets, notably the trade-off between housing price and time-on-the-market, the positive correlation between housing price and the number of contracts traded during a given period (i.e. the trading volume) and the existence of price dispersion.

This theoretical paper makes use of a search and matching model. Search and matching, indeed, are two fundamental characteristics of the trading process in the housing market, and, thus, the search-and-matching models have become the new economic approach to the analysis of real estate markets.

This paper shows that a slightly modified version of the baseline search and matching model à la Mortensen-Pissarides can explain the main empirical facts of housing markets. There are two key mechanisms that allow to achieve this notable goal: a simple formalisation of the (reasonable) assumption that buyers today are potential sellers tomorrow (and vice versa); and the direct relationship between market tightness and house price, derived by the standard matching model and underestimated by the related literature.

The developed theoretical model only studies the equilibrium conditions. Indeed, it would be interesting to also study the disequilibrium in housing markets.

The explanation of the main empirical facts of housing markets is embodied in the same and relatively simple theoretical model.

In addition to the explanation of the main empirical facts of housing markets, the developed theoretical model can generate an upward sloping Beveridge curve in the housing market (the positive relation between home-seekers and vacant houses). Instead, according to a recent criticism in the related literature, a model à la Mortensen-Pissarides inherently generates a (empirically unrealistic) downward sloping Beveridge curve.

In this paper, we evaluated the impact of the US “Chip Act” on the participation of the Chinese electronics industry in the global value chain based on the dynamic CGE model. This is a meaningful attempt to use the GTAP-VA model to analyze the electronics industry in China.

We employ a Dynamic GTAP-VA Model to quantitatively evaluate the economic repercussions of the “Chip Act” on the Chinese electronic industries' GVC participation from 2023 to 2040.

The findings depict a discernible contraction in China’s electronic sector by 2040, marked by a −2.95% change in output, a −3.50% alteration in exports and a 0.45% increment in imports. Concurrently, the U.S., EU and certain Asian economies exhibit expansions within the electronic sector, indicating a GVC realignment. The “Chip Act” implementation precipitates a significant divergence in GVC participation across different countries and industries, notably impacting the electronics sector.

Through a meticulous temporal analysis, this manuscript unveils the nuanced economic shifts within the GVC, substantially bridging the empirical void in existing literature. This narrative accentuates the profound implications of policy regulations on global trade dynamics, contributing to the discourse on international economic policy and industry evolution.

We evaluated the impact of the US “Chip Act” on the participation of the Chinese electronics industry in the global value chain based on the dynamic CGE model. This is a meaningful attempt to use the GTAP-VA model to analyze the electronics industry in China.

The interaction between policy regulations and global value chain (GVC) dynamics is pivotal in understanding the contemporary global trade framework, especially within technology-driven sectors. The US “Chips Act” represents a significant regulatory milestone with potential ramifications on the Chinese electronic industries' engagement in the GVC.

The significance of this paper is that it quantifies for the first time the impact of the US Chip Act on the GVC participation index of East Asian countries in the context of US-China decoupling. With careful consideration of strategic aspects, this paper substantially fills the empirical gap in the existing literature by presenting subtle economic changes within GVCs, highlighting the profound implications of policy regulation on global trade dynamics.

In international trade differences in political and legal systems confront trading partners with relatively greater information asymmetry and contract enforcement problems than in domestic trade, resulting in higher transaction costs. Nevertheless, well-functioning institutions in the exporting country could prove beneficial for the agricultural importer, as institutions generally establish food and product regulations and ensure that they are enforced and serve as a last resort for dispute resolution and contract enforcement. Given China’s increasingly stricter control of its food supply chain and its rising imports of meat products, the purpose of this paper is to analyze whether institutions in the exporting country matter for Chinese meat imports.

To analyze the effect of the exporters’ institutions on Chinese meat imports, the authors estimate a gravity model for the 1990-2013 period. The authors apply the method suggested by Helpman et al. (2008) to correct for sample selection and firm heterogeneity. To estimate the effect of time-invariant variables, the authors apply the Fixed Effects Vector Decomposition method proposed by Plümper and Troeger (2007).

The results show that institutions affect Chinese trade flows. In particular, the authors find that China imports more meat products from countries who host qualitatively better institutions and are geographically closer, and that the country’s imports rise with its GDP level. This confirms our hypothesis that institutions in the exporting country are positively associated with meat exports to China.

The importance of the exporters’ institutions for Chinese meat imports has not been studied so far and is of great interest given China’s rising role as a sizable importer. Furthermore, Chinese meat imports have attracted much attention recently due to the country’s potentially significant impact on world food security and sustainable development. Hence, this paper aims to make a substantial contribution to the literature, both from a scientific and a policy perspective.

The purpose of this study is to investigate international trade determinants, paying special attention to variables related to climate change and non-tariff measures (NTMs), as they shape more and more world trade flows, with particular incidence on globalised goods, such as wine.

Based on panel data of Port wine exports to 60 countries, between 2006 and 2018, a gravity model has been estimated through Poisson pseudo-maximum likelihood. Explanatory variables include NTMs, mean temperature, temperature anomaly, gross domestic product (GDP), exchange rate, ad valorem equivalent tariffs and home bias.

The findings show that exports are inversely related to both mean temperature and temperature anomaly in importing countries. Regarding NTMs, it is found that only part of them are trade deterrent. Additionally, purchasing power in importing countries is one of the main determinants of Port wine exports.

The results show that, besides traditional economic variables, policymakers and wineries should include in their exports' decisions the impact of variables related to climate change and NTMs.

The novelty of this paper is to incorporate the impact of climatic variability of importing countries as a determinant of international trade of wine. Most former studies inspired of the gravity model consider explanatory variables such as GDP and exchange rate, and more recent ones started to consider NTMs too, however, this study may be the first paper to include the impact of climate change (quantified by mean temperature and temperature anomaly in importing countries) on exports.

The paper is a preliminary assessment of coronavirus disease’s (COVID-19) effects on African trade, policy responses and opportunities within the limitations imposed by data and the information currently available and in the lights of other international organizations’ growth forecasts. The study was undertaken to get deeper understanding of the threats and opportunities of COVID-19 on African trade because of the existing interconnected trade networks making African countries to be more vulnerable and increasing number of restrictions and distortions among major traders. This study aims to present strong information required in underpinning sound national, regional and inter-regional policy responses to keep trade flowing.

To assess COVID-19’s effects on African trade, policy responses and opportunities, this study relied on data and information currently available from organizations such as World Trade Organization (WTO), World Bank (WB), Organisation for Economic Co-operation and Development, International Monetary Fund, European Union, International Trade Statistics and various African countries’ trade and national statistics publications. The analysis contains two main scenarios. The first, an observed effects scenario (first quarter of year 2020), looks at the observed effect of COVID-19 outbreak on trade in Africa. The second, a potential effects scenario, analyses the potential trade effects if the COVID-19 outbreak lingers and spreads more intensively than is assumed in the baseline scenario.

The COVID-19 outbreak affects several aspects of international trade even though the full effects of the outbreak are not yet visible in most trade data. Some leading indicators had shown that keeping trade flow can support the fight against COVID-19 as well as having damaging effect on Africa’s trade. COVID-19 had led to a deep fall in transaction, both at the international level and within-regions. Tariffs and other restrictions to imports harm the flow of critical products to African countries. Uncooperative trade policies lead to higher prices of goods in fragile and vulnerable African countries.

Long term in-depth analysis of the effects of COVID-19 on trade using quantitative data is still very difficult because of paucity of data and the great level of the improbability of the trajectory of the spread of the virus. Informed assessment of the full trade impact of the pandemic on African countries is therefore still difficult. Notwithstanding, this study assesses the immediate effects and conveys the likely extent of impending African trade pains and the potential needs for assistance.

Trade in both goods and services plays a key role in overcoming the pandemic and limit its effects by providing access to essential medical goods to treat those affected, ensuring access to food, providing farmers with needed inputs, support jobs and sustain economic activity during global recession. However, temporary COVID-19 trade measures such as borders closure, export prohibition and import ban are a threat to globalization and free trade agreements engaged by some African countries.

The continuous rise in COVID-19 cases is expected to trigger economic recession in Africa despite a rapid expansion and creation of new social protection programmes. The unavoidable decline in trade caused by COVID-19 is already having painful consequences on the economy, social anxiety among families, households, businesses and trade across countries in the continent. COVID-19 trade restrictions aimed at reducing the transmission of the virus have led to loss of income and jobs as well as closure of small and vulnerable businesses. Policymakers should enforce social policies that unite countries within the continents in bad times to reduce social anxiety and hardship.

Although the effects of COVID-19 outbreak on global and regional trade have received enormous attention recently, facts in the form of data have been thin particularly on African trade. This paper, to the best of the authors’ knowledge, is one of the first set of studies that provides preliminary assessment of COVID-19’s effects on trade in Africa using scenarios-building approach based on the available data and information on regional trade, complemented by those from the WTO, WB and departments of trade and statistics from various African countries such as the Nigeria Nation Bureau of Statistic and Kenyan National Bureau of Statistics.

This paper aims to pose an important starting point for the application of the search-and-matching models to real estate appraisals, thus reducing the “gap” between practitioners and academicians. Due to relevant trading frictions, the search-and-matching framework has become the benchmark theoretical model of the housing market. Starting from the large related literature, this paper develops a simplified approach to modelling the frictions that focuses on the direct relationship between house price and market tightness (a common feature only for the labour market matching models). The characterization of the equilibrium through two main variables simplifies the analysis and allows using the theoretical model for empirical purposes, namely, the real estate appraisals.

This work is both theoretical and empirical. Theoretically, a long-run equilibrium model with a positive share of vacant houses and home seekers is determined along with price and market tightness. Also, the conditions of existence and uniqueness of the steady-state equilibrium are determined. Unlike most of the search-and-matching models in the housing literature, the out-of-the steady-state dynamics are also analyzed to show the stability of the equilibrium. Empirically, to show the usefulness of the theoretical model, a numerical simulation is performed. By using two readily available housing market data – the expected time on the market and the average number of trades – it is possible to determine the key variables of the model: price, market tightness and matching opportunities for both buyers and sellers. Although the numerical simulation concerns the Italian housing market, the proposed model is generally valid, being empirically applicable to all real estate markets characterized by non-negligible trading frictions. Indeed, the proposed model can be used to compare housing markets with different features (concerning the search and matching process), as well as analyse the same housing market in different time periods (because the efficiency of the search and matching process can change).

Several important results are obtained. First, the price adjustment – i.e. the difference between the actual selling price and the price obtained in an ideal situation of frictionless housing market – is remarkable. This means that the sign and the size of the price adjustment depend on the extent of trading frictions in the housing market. Precisely, the higher the trading frictions on the demand side (more buyers and less sellers), the higher the actual selling price (the price adjustment is positive), whereas the higher the trading frictions on the supply side (less buyers and more sellers), the lower the actual selling price (the price adjustment is negative). Accordingly, the real estate appraisers should assess the trading frictions in the housing market before determining the price adjustment. Second, an increase in the number of trades affects the house price only if the time on the market varies. Also, the higher the variation in the time on the market, the larger the house price adjustment. Indeed, the expected time on the market reflects the opportunities to matching for both parties and thus the trading frictions. If the time on the market increases (decreases), the seller will receive less (more) opportunities to match; thus, the actual selling price will be driven downwards (upwards).

As far as the authors are aware, none of the existing works in the search and matching literature has considered how to take advantage of this theoretical approach to estimate the house price in the presence of trading frictions in the housing market. Indeed, the proposed theoretical model may be a useful tool for real estate appraisers, as it is able to derive the trading frictions from the time on the market and the number of trades, thus estimating properly the house price.

Many studies have shown that the intensity and the number of hurricanes are likely to increase. This paper aims to look at the immediate effects of hurricanes on the time on the market, share of houses sold and percentage of houses with price cuts in the housing market using the metropolitan statistical area-level data in Florida.

Using a difference-in-difference method, the authors estimate the impact that a hurricane has on the housing markets.

The authors find that a hurricane has a positive and significant effect on the time on the market. A hurricane leads to a delay of the sale of a typical house in Florida by five days. The authors test for within-year seasonality and show that these effects change with seasonality of the housing market. Markets with seasonal housing prices tend to be affected more by hurricanes than those where housing prices are not seasonal. The authors also show that effects of a hurricane are transient and fade away in a few months. The results remain significant as the hurricane intensity changes.

This is the first study to look at the short-term effects of the hurricanes and how their effects vary based on seasonality of the markets.

We examine the impact of market frictions in the form of trading costs on investor average holding periods for stocks in the S&P global 1200 index to examine constraints on international portfolio diversification.

We determine whether it is appropriate to pool stocks listed in the USA, Canada, Latin America, Europe, Japan, Asia and Australia into investigations using the same empirical specification. This is very important because the pooled effects may not provide consistent estimates of the average.

We report overwhelming econometric evidence that it is not valid to pool stocks in all the underlying regional equity indices for our investigation, indicating that the effect of frictions varies between markets.

When we pool the stocks within markets, we discover that for companies listed in the USA, Europe, Canada and Australia, market frictions do not significantly influence holding periods and hence are not a barrier to portfolio rebalancing. However, companies listed in Latin America and Asia face market frictions, which are significant in terms of increasing holding periods.

We ascertain that taking into account the properties of stock markets in different geographical locations is vital for understanding the limits on achieving international portfolio diversification.

Unlike prior research, we overcome the problems caused by contemporaneous correlation, endogeneity and joint determination of investor average holding periods and trading costs by employing the Generalized Method of Moments (GMM) system panel estimator. This makes our empirical estimates robust and more reliable than the previous empirical research in this area.

As foreign direct investment (FDI) plays an important role in economic globalization. This paper examines the structural features of the global FDI network based on FDI flows data and changes in the position of countries within the network.

In order to study the structural characteristics of the global FDI network and the status and changes of countries in the global FDI network, the authors build the investment network and apply the QAP (Quadratic Assignment Procedure) analysis to examine the evolutionary characteristics of the network and its influencing factors.

The global FDI network becomes more interconnected and has a clear “core-periphery” structure. The network connections and volumes have increased dramatically and most countries spread their assets across multiple countries, while only a handful of countries have concentrated investments. The topological structure of the global FDI network has changed noticeably, although this process has been slow and stable and countries in the core position have remained largely intact. The authors find that trade relations between countries, geographic distance and differences in economic size, income levels and institutional environments all have a significant impact on the global FDI network.

Although we find some valuable results, some aspects need further investigation. For example, how a country uses the investment network to boost its economy and how the different industries in the investment network change over time. It is important to get the industry-level details to understand the impact of the global investment network from a government's perspective.

FDI affects the distribution of international capital and contributes to the development of the global economy. Therefore, it is important to study the characteristics of the global FDI network and its development patterns. With more understanding about the network as well as its evolutionary pattern, the government can possibly carry out some policies to promote direct investments as well as economic development.

All countries should actively engage in international direct investments and strengthen their economic ties. At the same time, they can put more emphasis on inward or outward FDI based on their own level of economic development to better establish the circulation channel for domestic and international capital.

This paper examines foreign direct investments through the lens of a global network. In contrast to traditional bilateral studies, this paper focuses on the network structure and evolution, reflecting the dynamics of the entire direct investment system as well as the changing positions of participating countries.

Whatever happened to retail trade area analysis? Some may recall that through the late 1950s and middle 1960s, location scholars seemed to be organising and expanding an interesting body of literature. However in the recent past, the central thrust of economic analysis seems to have stalled, with research dispersing in numerous directions.