Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices

Setting sale prices correctly is of great importance for firms, and the study and forecast of prices time series is therefore a relevant topic not only from a data science perspective but also from an economic and applicative one. In this paper, we examine different techniques to forecast sale prices applied by an Italian food wholesaler, as a step towards the automation of pricing tasks usually taken care by human workforce. We consider ARIMA models and compare them to Prophet, a scalable forecasting tool by Facebook based on a generalized additive model, and to deep learning models exploiting Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNNs). ARIMA models are frequently used in econometric analyses, providing a good benchmark for the problem under study. Our results indicate that ARIMA models and LSTM neural networks perform similarly for the forecasting task under consideration, while the combination of CNNs and LSTMs attains the best overall accuracy, but requires more time to be tuned. On the contrary, Prophet is quick and easy to use, but considerably less accurate.

Econometric Analysis of Dutch Disease Implication of China-Africa Trade

This study revisits the analysis of the Dutch disease implication of China-Africa trade for Africa’s non-mineral resources sectors; specifically, manufacturing and agricultural sectors, while focusing on the trade relationship between China and 27 African countries for the period of 19years, 2001 to 2019. This prompted an econometric analysis with the use of two-step dynamic (difference and system) panel Generalized Method of Moment (GMM) models, which was also complemented with dynamic least squares panel econometric regression. The preliminary analysis revealed that Ethiopia is the largest African trading partner with China, with an average of about 21percent China-Ethiopia trade ratio, while Botswana has the least trade relation with China, with 1.5percent Botswana-China trade ratio. The result of our econometric analyses suggests that higher China-Africa trade has the potential to reduce Africa’s manufacturing value-added. In other words, China-Africa trade is not causing Dutch disease in Africa but has the potential to cause Dutch disease in the future. Furthermore, the result suggests that higher China-Africa trade has the potential to increase Africa’s agricultural sector productivity. This implies that China-Africa trade has no tendency of causing Dutch disease in the agricultural sector. Our results are robust to different data structures for the dynamic GMM model.

The Performance Rewards of Human Capital Development in the Federal Government

Human capital is one of the most vital assets an organization possesses. Research has demonstrated that human capital is directly related to performance. Thus, there is a clear incentive for organizations to grow their human capital levels. Not surprisingly, then, organizations have created and employed a wide variety of managerial practices focused on further developing human capital within their employees. Yet even as the U.S. government faces forthcoming human capital shortages due to the ongoing retirements of a large segment of its workforce, empirical research investigating the impact of commonly used human capital development practices on performance in the public sector is scarce. Therefore, to gain a deeper understanding of this dynamic relationship, using U.S. federal personnel data, this study analyzes the impact of human capital development practices on agency performance. The results of longitudinal econometric analyses suggest that human capital development practices have positive effects on agency performance.

The impact of macroeconomic and structural factors on the unemployment of young women and men

The presented article follows the research mainstream of econometric analyses focused on the assessment of correlations between youth unemployment rate and market and macroeconomic determinants, including economic growth and productivity of the economy, its structure in terms of NACE Rev.2 sections as well as the labor market tools. The research addresses 28 European Union (EU) countries. The analysis period covers the years 2008–2018. The econometric methods dedicated to panel data were used. The research results confirm the importance of the general economic condition as well as the development of knowledge-based economy for the improvement of the youth situation in the labor market. With regard to the economy structure, the development of manufacturing section importance turned out to be a major factor in female youth unemployment rate reduction. The growing importance of the construction sector translated into a decline in the unemployment rate among young men.

Differentiation of Fiscal Effects of Local Tax Policy in Countries Using Area-Based Property Taxation: the Case of Poland

The paper addresses differences in financial effects of local tax policy. Its aim was to examine the effects of decisions taken within the realm of tax authority in a country which applies area-based property taxation. The paper validates the hypothesis, according to which the impact of local tax policy upon tax revenues of local units depends on the social and economic potential of regions (in Poland called “voivodeships”). We believe that municipalities (called “gminas” in Polish) are more active in pursuing local tax policy (i.e., in reducing property tax rates) in regions whose social and economic position is weaker. Statistical and econometric analyses confirmed our theoretical assumptions and provided the evidence that the hypothesis is correct. By using econometric models, in this paper we also succeeded in identifying variables which help in explaining the real scale of reductions of property tax rates.

Write Like a Pro or an Amateur? Effect of Medical Language Formality

Past years have seen rising engagement among caregivers in online health communities. Although studies indicate that this caregiver-generated online health information benefits patients, how such information can be perceived easily and correctly remains unclear. This study aims to fill this gap by exploring mechanisms to improve the perceived helpfulness of online health information. We propose a multi-method framework, including a novel Medical-Enriched DEep Learning (MEDEL) feature extraction method, econometric analyses, and a randomized experiment. The results show that when the medical language of health information is informal, the senior care information is more helpful. Our findings provide a theoretical foundation to understand the influence of language formality on many other business communications. Our proposed multi-method approach can also be generalized to investigate research questions involving complex textual features. Forum sites could leverage our proposed approach to improve the helpfulness of online health information and user satisfaction.

Let Photos Speak: The Effect of User-Generated Visual Content on Hotel Review Helpfulness

A picture is worth a thousand words. User-generated photos (UGPs) are increasingly accompanying online reviews of hotels. This article draws on media richness theory to estimate the effects of UGPs on hotel reviews’ helpfulness. Based on a sample of 1,159,590 valid reviews with 464,316 photos, we utilized an integrated analytical model incorporating both econometric analyses and image-processing techniques. The results show that reviews accompanied by UGPs are generally rated as more helpful than those with textual content only. Furthermore, photos showing guestroom objects were rated as more helpful than those showing food & beverages. Finally, the positive effects of UGPs on review helpfulness were especially prominent for hotels with lower prices and negative reviews. This study adds new insights to the online review literature and advances the methodological approach in analyzing unstructured user-generated content. This study provides important implications for hotel managers and online booking platforms regarding UGP management.

What Can Go Wrong When Western Companies Invest in Poor Nations

This chapter examines the case of multinational corporations to demonstrate how the West is still causing economic damage to poor nations. Multinational corporations are companies that are based in one country but have subsidiaries in many other nations of the world. Multinational corporations investing in poor nations is supposed to be good; the multinational corporations offer to bring in capital and technology, which are just what struggling economies need. The problem is capital repatriation, which is when a foreign-owned subsidiary of a multinational corporation transfers its profits out of the local country and into the home country where the multinational's headquarters are located. The chapter then considers a famous study by Barnet and Muller of the Latin American subsidiaries of American manufacturing companies in the 1960s. They found that the American companies actually started very few new manufacturing operations in Latin America. They instead shopped for preexisting successful companies, taking operations that already had a substantial income flow and diverted that flow to the United States. Meanwhile, econometric analyses of both the short-term and the long-term effects of foreign direct investment find that the turnaround point is about five years after the investment. From year zero to year five, foreign direct investment raises rates of economic growth. From year five to year twenty, foreign direct investment lowers rates of economic growth.

The Contribution of SME to Regional Economic Development: On example of Adjara Autonomous Republic

Small and medium entrepreneurship (SME) is one of the most important sectors of the national economy. It determines the economic growth rate of the country/region and the structure of the gross national product. The article aims at evaluating the contribution of SME to the regional economic development on example Adjara A.R. (Republic of Georgia), investigating and analyzing importance of SME development at regional level and discussing the factors influence on its development. In the research section of the given article econometric analyses of SME key indicators is conducted by linear log-regression model based on statistical data of 2006-2019 years. The results of the research study show positive impacts of the number of employees and their productivity on gross value added. The study aims at underlining the government policy supporting an advantageous SME environment and conditions, which is a precondition for regional economic development.