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Brazil uses the dollar as a vehicle currency to invoice its exports. This fact produces a tendency toward equalizing the prices of products in dollars in the international market and reducing the ability of firms to practice pricing-to-market (PTM). This study aims to evaluate the hypothesis by estimating error correction models in panel data, obtaining estimates of PTM for 25 manufacturing products exported by Brazil between 2010 and 2020.

This study uses the correlated common effect estimator proposed by Pesaran (2006) and Chudik and Pesaran (2015b) to estimate the PTM coefficients.

Results of this study indicate that exporters practice local-currency pricing stability for dollar prices. This study obtains that Brazilian exporters tend to stabilize their dollar price for exports, reducing heterogeneity between destination markets. The results are in agreement with the hypothesis of the prevalence of the coalescing effect of Goldberg and Tille (2008) and lower sensitivity of the markup adjustment to the specific market, as pointed out by Corsetti et al. (2018). The pricing of Brazilian exports in dollars reflects a profit maximization strategy that considers an international price system based on global demand for products.

In addition to analyzing the dollar role in the pricing of Brazilian exports through the triangular decomposition, this study also shows the importance of examining the cross-section dependence of errors, considering the heterogeneous cointegration in export pricing models and producing PTM estimates for short-term and long-term.

This paper aims to investigate the role of price-based information from major cryptocurrencies, foreign exchange, equity markets and key commodities in predicting the next-minute Bitcoin (BTC) price. This study answers the following research questions: What is the best sparse regression model to predict the next-minute price of BTC? What are the key drivers of the BTC price in high-frequency trading?

Least absolute shrinkage and selection operator and Ridge regressions are adopted using minute-based open-high-low-close prices, volume and trade count for eight major cryptos, global stock market indices, foreign currency pairs, crude oil and gold price information for February 2020–March 2021. This study also examines whether there was any significant break and how the accuracy of the selected models was impacted.

Findings suggest that Ridge regression is the most effective model for predicting next-minute BTC prices based on BTC-related covariates such as BTC-open, BTC-high and BTC-low, with a moderate amount of regularization. While BTC-based covariates BTC-open and BTC-low were most significant in predicting BTC closing prices during stable periods, BTC-open and BTC-high were most important during volatile periods. Overall findings suggest that BTC’s price information is the most helpful to predict its next-minute closing price after considering various other asset classes’ price information.

To the best of the authors’ knowledge, this is the first paper to identify the covariates of major cryptocurrencies and predict the next-minute BTC crypto price, with a focus on both crypto-asset and cross-market information.

While much of the literature testing for shirking by professional athletes have used performance metrics, some works have quantified shirking in dollar terms by comparing salary to estimated marginal revenue product (MRP). However, Ordinary Least Squares (OLS) approaches to measuring shirking by comparing salary to MRP have an endogeneity problem, as salary and contract length are determined simultaneously. We test for shirking in Major League Baseball (MLB) using an MRP approach, addressing this potential endogeneity.

This paper uses instrumental variables regression to address potential endogeneity using MLB season-level player and team data from 2010 to 2017.

Using OLS regression, the impact of an additional year of guaranteed contract on shirking is estimated at approximately $1m in 2010 US dollars, and the impact of having a long-term contract is estimated at $5m, estimates comparable to those in the literature. Using instrumental variables regression, these impacts increase to $1.6m and over $9m in 2010 dollars.

Given large, causal shirking estimates, profit maximizing sports organizations should take caution when negotiating long-term contracts. These findings also have important implications for other labor market settings where workers feel job security.

To our knowledge, this is the first work testing for shirking in sports using an MRP approach which uses instrumental variables regression to address potential endogeneity.

The authors investigate the impact of the US stock market on the economies of the BRICS and major industrialized economies (G7).

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. Global vector autoregressive (GVAR) empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The authors summarize the results in four points: (1) financial integration variables increase the effect of the US stock market on the BRICS and G7, (2) the US shock produces similar responses in these groups regarding industrial production, stock markets and confidence but different responses regarding domestic currencies: in the BRICS, the authors detect appreciation of the currencies, while in the G7, the authors find depreciation, (3) G7 stock markets and policy rates are more sensitive to the US shock than the BRICS and (4) the estimates point out to heterogeneities such as the importance of industrial production to the transmission shock in Japan and China, the exchange rate to India, Japan and the UK, the interest rates to the Eurozone and the UK and confidence to Brazil, South Africa and Canada.

The results reinforce the importance of taking into account different levels of economic development.

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. GVAR empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

It is documented that companies and government agencies in the USA invest more in the fourth fiscal quarter without having higher investment opportunities. While previous studies focus on the agency conflicts and information asymmetry within organizations, this study is motivated by Scharfstein and Stein's (2000) two-tiered agency model and aims to examine how firms' external business environment affects the “fourth quarter effect.”

The authors implement this study in a sample of 41 countries and observe similar seasonality in firm investment as documented in the US market.

More importantly, using country characteristics, this study finds that firms from countries with better investor rights and protection, and more developed financial markets show less severe over-investment in the fourth fiscal quarter.

This paper contributes to the literature of law and finance, and the internal capital market, by investigating the quarterly investment patterns of firms from 41 countries. The authors find that similar to the results in earlier studies on the US market, firms in the global market increase their capital expenditure in the fourth fiscal quarter, indicating that the internal agency conflicts between the headquarters and divisional managers are widespread across the world. The authors also find that firms that operate in countries with higher investor rights and protection, and more developed financial markets, tend to show less severe “fourth quarter effect”.

It has been suggested that homicides in Jamaica are partly driven by conflicts among criminals over funds coming from international lottery scams; most of these funds are channeled into the country via remittances. This study aims to determine the empirical relationship between remittances and homicides in Jamaica over the period 1985–2019.

The authors apply an error correction modelling framework while accounting for indicators of changes in socioeconomic conditions.

There are two. First, the authors find from impulse response analysis of the long-run dynamics that an increase in remittances is associated with an increase in homicides, and vice versa. Second, the authors find that there is bidirectional Granger causality between remittances and homicides in the short run.

Two important implications are that policies should be strengthened to channel remittances to productive and legal investment opportunities and that greater efforts may be needed to stem the flow of funds coming from international lottery scamming and other illegal activities.

This is the first study that examines the dynamic relationship between remittances and homicides in Jamaica from a robust statistical perspective.

In this paper we examine the validity of the J-curve hypothesis in four Southeast Asian economies (Indonesia, Malaysia, the Philippines and Thailand) over the 1980–2017 period.

We employ the linear autoregressive distributed lags (ARDL) model that captures the dynamic relationships between the variables and additionally use the nonlinear ARDL model that considers the asymmetric effects of the real exchange rate changes.

The estimated models were diagnostically sound, and the variables were found to be cointegrated. However, with the exception of Malaysia, the short- and long-run relationships did not attest to the presence of the J-curve effect. The trade flows were affected asymmetrically in Malaysia and the Philippines, suggesting the appropriateness of nonlinear ARDL in these countries.

The previous research tended to examine the effects of the real exchange rate changes on the agricultural trade balance and specifically the J-curve effect (deterioration of the trade balance followed by its improvement) in the developed economies and rarely in the developing ones. In this paper, we address this omission.

The purpose of this research is to primarily understand how crypto traders can use the Bitcoin as a hedge or safe haven asset to reduce their losses from crypto trading. The study also aims to provide insights to crypto investors (portfolio managers) who wish to maintain a crypto portfolio for the medium term and can use the Bitcoin to minimize their losses. The findings of this research can also be used by policymakers and regulators for accommodating the Bitcoin as a medium of exchange, considering its safe haven nature.

This study applies the cross-quantilogram (CQ) approach introduced by Han et al. (2016) to examine the safe-haven property of the Bitcoin against the other selected crypto assets. This method is robust for estimating bivariate volatility spillover between two markets given unusual distributions and extreme observations. The CQ method is capable of calculating the magnitude of the shock from one market to another under different quantiles. Additionally, this method is suitable for fat-tailed distributions. Finally, the method allows anticipating long lags to evaluate the strength of the relationship between two variables in terms of durations and directions simultaneously.

The Bitcoin acts as a weak safe haven asset for a majority of new crypto assets for the entire study period. These results hold even during greed and fear sentiments in the crypto market. The Bitcoin has the ability to protect crypto assets from sharp downturns in the crypto market and hence gives crypto traders some respite when trading in a highly volatile asset class.

This study is the first attempt to show how the Bitcoin can act as a true matriarch/patriarch for crypto assets and protect them during market turmoil. This study presents a clear and concise representation of this relationship via heatmaps constructed from CQ analysis, depicting the quantile dependence association between the Bitcoin and other crypto assets. The uniqueness of this study also lies in the fact that it assesses the protective properties of the Bitcoin not only for the entire sample period but also specifically during periods of greed and fear in the crypto market.

The Polish economy has undergone major challenges and changes over the past few decades. The country's trade flows, in particular, have become more firmly tied to the country’s Western neighbors as they have grown in volume. This study examines Poland's trade balances in ten Standard International Trade Classification (SITC) sectors versus the United States of America, first testing for and isolating structural breaks in each time series. These breaks are then included in a set of the cointegration models to examine their macroeconomic determinants.

Linear and nonlinear and nonlinear autoregressive distributed lag models, both with and without dummies corresponding to structural breaks, are estimated.

One key finding is that incorporating these breaks reduces the significance of the real exchange rate in the model, supporting the hypothesis that this variable already incorporates important information. It also results in weaker evidence for cointegration of all variables in certain sectors.

This study looks only at one pair of countries, without any third-country effects.

An important country pair's trade relations is examined; in addition, the real exchange rate is shown to incorporate economic information that results in structural changes in the economy. The paper extends the existing literature by conducting an analysis of Poland's trade balances with the USA, which have not been studied in such a context so far. A strong point is a broad methodology that lets compare the results the authors obtained with different kinds of models, both linear and nonlinear ones, with and without structural breaks.

This paper aims to obtain a recent estimate of the cost of precautionary foreign reserve accumulation that emerging market and developing economies (EMDEs) had to endure to protect themselves against the risks of financial globalization. In addition, the study estimates the cost of excess reserves in emerging market economies (EMEs) using various reserve adequacy indicators that reflect potential sources of foreign exchange drains and vulnerability in EMEs' balance of payments.

This paper begins by explaining the accumulation of foreign reserves in EMDEs as a self-protection strategy against the risks of financial globalization. Next, it sheds light on the different types of economic costs of foreign reserve accumulation. Finally, it estimates the cost of foreign reserve accumulation in EMEs during the period (1990–2018) and in EMDEs during the period (1990–2015) due to data availability.

Results indicate that the cost of accumulating foreign reserves as a self-protection strategy in EMDEs and EMEs' was huge compared to their development financing needs. Applying various reserve adequacy measures demonstrates that many of the EMEs were holding inadequate precautionary reserves in 2018. Actually, this reflects the significant increase in external short term debt that many of the EMEs have witnessed since the eruption of the global financial crisis (2008). Thus increasing reserves in EMEs with weak reserve buffers and higher external debt is critical as they are more vulnerable to external shocks and capital flow reversals. Also given the estimated huge costs of accumulating foreign reserves, EMDEs should accompany it by other complementary self-protection policies and liquidity management policies to free up resources for productive investment.

The study contributes to the literature by estimating the cost of precautionary foreign reserve accumulation imposed on EMDEs during an extended period of time that covers a decade after the onset of the global financial crisis. Also to the authors' knowledge, this is the first study that estimates the cost of excess reserves in EMEs using various reserve adequacy indicators including the International Monetary Fund (IMF) assessing reserve adequacy (ARA) approach.