This paper aims at reexamining external sustainability in a dynamic framework for nine European Monetary Union (EMU) countries during the period 1970–2021. We extend the approach of Bohn (1998) to a time-varying external reaction function. The main advantage of our empirical strategy is that it captures the dynamics of the external reaction function, by accounting for the main sources of heterogeneity among EMU countries and by including common factors like financial globalization and global risk aversion. To estimate the model, we employ a fully fledged state-space framework, which extends the simple model generally used in this literature to a panel-data time-varying parameter framework, combining fixed (common and country-specific) and varying components. Our results show an evident interplay between real and financial variables, the latter progressively increasing their importance. Although heterogeneous, the adjustment to external imbalances in most EU countries is jointly driven by the level reached in the stock of net foreign assets together with the degree of risk aversion and financial openness.

This paper investigates both conditional and unconditional convergence in labor productivity within the manufacturing industries of the Eurozone over the period 1963 – 2018. We employ two innovative models: constant and varying-coefficient hierarchical panel data convergence regression models, each equipped with two sets of latent factor structures—one comprising global factors and the other industry-specific factors. These models offer distinct advantages, allowing for both global and industry-specific cross-sectional dependencies and permitting parameter heterogeneity across individual industries. Our findings reveal both conditional and unconditional convergence across the manufacturing industry as a whole, as well as among the majority of the 23 sub-manufacturing industries at the ISIC two-digit level. Moreover, we observe significant variation in convergence dynamics among these sub-manufacturing industries. Robustness checks, performed across different subperiods, confirm the reliability of our results. Furthermore, a comparison of our model’s outcomes with those of two alternative models provides additional support for our conclusions.

Wine is the most differentiated of all farm products, with much of the differentiation based on the location of production. In this paper, we estimate the effects of climate and vintage weather on California's varietal wine quality and prices. Our analysis is based on a sample of premium wines rated by Wine Spectator magazine between 1994 and 2022 and a comparable sample of secondary market auction prices from K&L Wine Merchants, each matched to spatially detailed weather data from PRISM. We find that extreme temperatures, particularly extremely hot temperatures, caused prices to decline. Absent additional adaptation, climate change will harm wine quality and disrupt quality signals from geographical indications in California's premier wine regions.

The aim of this paper is to analyse the role of climate change on state fragility in sub-Saharan Africa (SSA). To do this, we estimate a country-time fixed effects panel data model using the two-way fixed effects estimator over the period 1995 to 2020 for 45 SSA countries. Our results show that climate change increases fragility in SSA; specifically, rising temperatures and decreasing rainfall increase the social, economic, political and security fragility of SSA countries. The study also reveals that gross domestic product, population growth, migrant remittances, foreign direct investment, natural resources, inflation and agricultural price volatility are mechanisms through which climate change exacerbates state fragility. Based on these results, we recommend climate change adaptation measures such as increasing water storage to cope with periods of extreme drought, growing climate-smart crops, and the introduction of environmental public policies.

Data from a risky choice experiment are used to estimate a fully parametric stochastic model of risky choice. As is usual with such analyses, Expected Utility Theory is rejected in favour of a form of Rank Dependent Theory. Then an estimate of the risk aversion parameter is deduced for each subject, and this is used to construct a measure of the “closeness to indifference” of each subject in each choice problem. This measure is then used as an explanatory variable in a random effects model of decision time, with other explanatory variables being the complexity of the problem, the financial incentives, and the amount of experience accumulated at the time of performing the task. The most interesting finding is that significantly more effort is allocated to problems in which subjects are close to indifference. This presents us with another reason (in addition to statistical information considerations) why such tasks should play a prominent role in experiments.

The classical trinity of tests is used to check for the presence of a tremble in economic experiments in which the response variable is binary. A tremble is said to occur when an agent makes a decision completely at random, without regard to the values taken by the explanatory variables. The properties of the tests are discussed, and an extension of the methodology is used to test for the presence of a tremble in binary panel data from a well-known economic experiment.

We provide the first, in experimental economics, consistent estimates of a dynamic learning model with a continuous outcome. The econometric approach we propose can be used in many experimental studies including auctions, bargaining with transfers, and gift exchange experiments. We focus on affiliated private value auctions, where subjects are generally assumed to converge to the rule-of-thumb bidding, but our general approach is applicable to many other settings. Our IV estimates suggest that subjects become significantly less aggressive over time; specifically, they decrease their bids in proportion to the previous period’s signal minus bid. However, the inconsistent OLS and FE estimators imply that subjects become significantly more aggressive over time—they raise their bids in proportion to the previous period’s signal minus bid. Our instruments are randomly generated by the experiment, and pass popular weak instrument tests.

This paper specifies the panel data experimental design condition under which ordinary least squares, fixed effects, and random effects estimators yield identical estimates of treatment effects. This condition is relevant to the large body of laboratory experimental research that generates panel data. Although the point estimates and the true standard errors of the estimated average treatment effects are identical across the three estimators, the estimated standard errors differ. A standard F test as well as asymptotic reasoning guide the choice of which estimated standard errors are the appropriate ones to use for statistical inference.

Relying upon an original (country-sector-year) measure of robotic capital ($RK$), we investigate the degree of complementarity/substitutability between robots and workers at different skill levels. We employ nonparametric methods to estimate elasticity of substitution patterns between $RK$ and skilled/unskilled labor over the period 1995–2009. We show that: i) on average, $RK$ exhibits less substitutability with skilled workers compared to unskilled workers, indicating a phenomenon of “RK-Skill complementarity”. This pattern holds in a global context characterized by significant heterogeneity; ii) the dynamic of “RK-Skill complementarity” has increased since the early 2000s; iii) the observed strengthening is more prominent in OECD countries, as opposed to non-OECD countries, and in the Manufacturing sector, compared to non-Manufacturing industries.

Our paper sheds light on Sanitary and Phytosanitary (SPS) cooperation among trading countries. We contribute to the existing literature a data-driven analysis on the effectiveness of various forms (in monetary value, duration, and diversification) of SPS related technical assistance received by 33 countries from 1993 to 2015. The World Trade Organization's (WTO's) SPS Agreement encourages biosecurity for countries through technical assistance, to safeguard human health and productivity from contamination by biological hazards (pests, pathogens, or invasive species). Our panel model finds that WTO's SPS program encourages simultaneously agricultural trade and biosecurity. We implement a Multiple Indicator Solution (MIS) to correct bias from the endogenous technical assistance. The effectiveness of technical assistance depends on geography and the level of development among the heterogeneous countries referred to in our data. This investment in biosecurity benefits both donors and recipients of technical assistance. Based on our results donors should be encouraged to invest in countries with below average resources and abilities.

Much historical yield-monitor data is from fields where a uniform rate of nitrogen was applied. A new approach is proposed using this data to get site-specific nitrogen recommendations. Bayesian methods are used to estimate a linear plateau model where only the plateau is spatially varying. The model is then illustrated by using it to make site-specific nitrogen recommendations for corn production in Mississippi. The in-sample recommendations generated by this approach return an estimated $9/acre on the example field. The long-term goal is to combine this information with other information such as remote sensing measurements.

This article combines cross-national statistical analysis and in-depth historical case studies of Argentina and Chile to explore the relationship between two crucial dimensions of state capacity. We show that information capacity contributes to the development of fiscal capacity. When states have accurate information about their subject populations, territories, and economies, they are more effective at mobilizing revenues. In developing this argument this article makes three broader contributions. First, while existing scholarship either treats distinct dimensions of state capacity as separate entities, or simply assumes that they complement each other, our findings urge scholars to treat state development as sequential and to further investigate how multiple dimensions of state capacity are interrelated. Second, the paper suggests a broader underlying set of mechanisms – economies of scope – which connect these dimensions, and explores them in the specific context of how information capacity facilitates fiscal capacity. Third, we join the scholarship on the importance of societal compliance in the creation of the fiscal state, but with a focus on elite cooperation with the state's information collection efforts, which we show to be crucial to tax state development.

We examine the effect of corruption control on efficiency and its implications for efficiency spillovers by a stochastic frontier model. Our dataset covers 102 countries from 1996 to 2014. We find a positive relationship between corruption control and efficiency. If neighboring countries have difficulty in handling corruption, the country would be negatively affected by its neighbors' corruption through efficiency spillovers. We then compare the efficiency differences across countries for three time periods: 1996–2002, 2002–2008, and 2008–2014. On average, technical efficiencies slightly increased in the second period compared to the first period. In the third period, the efficiencies declined, particularly in China.

This study analyses firms’ labour demand when employers have at least some monopsony power. It is argued that without taking into account (quasi-)monopsonistic structures of the labour market, wrong predictions are made about the effects of minimum wages. Using switching fractional panel probit regressions with German establishment data, I find that slightly more than 80% of establishments exercise some degree of monopsony power in their demand for low-skilled workers. The outcome suggests that a 1% increase in payments for low-skilled workers would, in these firms, increase employment for this group by 1.12%, while firms without monopsony power reduce the number of low-skilled, by about 1.63% for the same increase in remuneration. The study can probably also be used to explain the limited employment effects of the introduction of a statutory minimum wage in Germany and thus leads to a better understanding of the labour market for low-skilled workers.

Inflation rates and their convergence within Euro area have been a major concern, since well before the advent of the single currency. Inflation differentials are a normal phenomenon in any monetary union and even in long-established monetary unions. The aim of this research is to examine the main factors of inflation differentials in the Euro-zone for the period 1999–2018. Our empirical estimates appear to suggest that a one-percentage-point increase in the positive output gap typically leads to an increase of about 20 basis points in the inflation rate of EMU countries. We also find three structural breaks, in 2004, 2008 and in 2010. Since the monetary policy of the European Central Bank is geared at maintaining low and stable inflation, the productivity growth should be increased, and the real effective exchange rates should be decreased and become more homogeneous among EMU. Therefore, countries’ inflation differentials may become less persistent.

We investigate the impact of five types of subsidies granted under the European Union Common Agricultural Policy on the persistent and transient inefficiency of Polish dairy farms. Our research shows that coupled and environmental subsidies reduce transient technical inefficiency, while the opposite is true for Less Favoured Areas (LFA) and other rural subsidies. Simultaneously, environmental, LFA, and other rural subsidies increase persistent technical inefficiency. These results imply that the impact of each type of subsidy on technical efficiency can be different and that the effect of the particular type of subsidy can vary between transient and persistent technical inefficiency.

Wine investment returns can come from overall market trends or price increases with age. Because of the short wine price histories available, market and maturation effects are difficult to separate. Consequently, researchers often obtain dramatically different estimates of investment returns. We find that data sample bias may be the hidden cause of the disparate estimates. In wine auction data, the sample bias refers to a shift in the distribution of which wines are traded as a function of their age. Such sample bias in panel data sampled across many different wine labels can distort the estimation of price increases versus age and consequently impact the estimation of market trends. This analysis shows that segmenting the analysis such that the data panels contain wine labels with similar trading characteristics can lead to a more stable estimation.

The analysis here looks at data from Bordeaux, Italy, Australia, and California. An Age-Period-Cohort (APC) analysis is applied to data panels from each region. Then the data in each region is segmented by a measure of popularity in order to reduce sampling bias. Data thus segmented is then re-analyzed to demonstrate the difference in estimating price appreciation lifecycles and market trends.

This study investigates the determinants of coffee prices received by growers in Costa Rica, paying attention to the impact of environmental, regional, quality, and international aspects in a panel data set for the period 2008–2016. We identify three groups of variables that affect domestic coffee prices. Some of them are external to the control of the coffee growers, such as the international price of green coffee or the power of multinationals; others, such as the altitude where the coffee is harvested or the berries' yield, are related to coffee quality but difficult to modify by coffee growers. The focus of our study is on the third group, which refers to differentiation strategies related to environmental certifications. More specifically, we consider two particularly relevant certifications, which are Fairtrade mills and organic coffee. We find that organic coffee berries received higher prices, but Fairtrade mills report lower average prices than other, non-certified, buyers.

The relationship between temperature and agriculture outcomes in Brazil has been widely explored, overlooking the fact that most of the country's labor force is employed in non-agriculture sectors. We use monthly individual-level panel data spanning the period from January 2015 to December 2016 to ask whether temperature shocks impact non-agriculture wages in formal labor markets. Our results show that additional days in a month that fall within high-temperature ranges have significant adverse effects on real wages. Assuming a uniform climate change scenario where the daily temperature distribution shifts by 2$^{\circ }$C, we calculate income losses for formal workers in non-agriculture markets equivalent to 0.12 per cent of 2015 GDP.