Business Survey Research Articles

H-2B Guest Workers and the Critical Role They Play in US Forests

AbstractA survey of businesses that provide a variety of forest management services indicated the importance of H-2B guest workers in performing important tasks which facilitate management and sustainability of forest resources in the United States. Those workers accomplish a wide variety of tasks with tree planting being most common. Although the positions filled by those workers are first made available to US workers at government-mandated wage rates, few apply. Businesses reported that it is becoming increasingly difficult for them to secure all of their guest visas to fulfill their contacts. Although former President Donald J. Trump’s proclamation on June 22, 2020, suspending entry of workers with H-2B visas, would have resulted in approximately one million acres not being reforested by respondents in 2020, a National Interest Exemption process provided a reprieve through the end of 2020. A long-term solution is needed to ensure that there are enough H-2B workers available to continue providing these important services.

Business Elites and European Integration: Really a Honeymoon Story?

AbstractThe question whether elites contribute constructively to the process of European integration has become more crucial today in times of increasing Euroscepticism and populist opposition to the European Union in the member states. In this article we venture off beaten paths and focus on a hitherto much less investigated segment of society, business elites, and particularly on their attitudes towards the process of European integration. For this purpose, we focus on a cross‐national survey of business elites with data from ten European countries. We show that levels of support for European integration are uneven across countries. At the same time, applying regression analysis, we find that the ways in which business elites shape their attitudes towards the European Union are not so different from those of public opinion, as individual‐level factors are more influential on their attitudes than are the structural properties of their companies.

The Impact of Climate Change on Farm Business Performance in Western Australia. Understanding Farmer’s Adaptation Responses and Their Key Characteristics in Response to a Changing and Variable Climate

This study examines ten years of financial and production data of 249 farm businesses operating in southwestern Australia. It also identifies the behavioural characteristics of the farm operators through a comprehensive socio-managerial survey of each farm business. The study area has a Mediterranean climate, where three quarters of the rainfall is received during the growing season from April and October. Growers have learned to produce 2 tonnes per hectare of wheat on less than 200 ml of growing season rainfall. Australia is the driest continent in the world and is renowned for its climate variability. In addition, evidence is emerging that its southern parts, like south-western Australia, are experiencing a warming, drying trend in their climate. Average annual rainfall over the last thirty years in the study area has declined and average minimum and maximum temperatures have risen. Moreover, in the last ten years a number of droughts have occurred. This multidisciplinary study examines the business performance of 249 farms from 2002 to 2011 and identifies the strategies farm managers have adopted to adapt to a drying, warming environment. Farms are categorised according to their performance. Their characteristics are compared and contrasted. We find many significant differences between farm performance categories and the adaptation strategies used by the farmers in each category. There are also different socio-managerial and behavioural characteristics between the groups of farmers identified.

Frequency domain analysis and filtering of business and consumer survey expectations

The main objective of this study is two-fold. First, we aim to detect the underlying existing periodicities in business and consumer survey expectations through spectral analysis. We use the Welch method to extract the harmonic components that correspond to the cyclic and seasonal patterns in all response options of monthly survey indicators. We find that business survey indicators show a common cyclical component of low frequency that corresponds to about four years, while for most consumer survey indicators, we do not detect any relevant cyclic components, and the obtained lower frequency periodicities show a very irregular pattern across questions and reply options. Second, we aim to provide researchers with a filter specially designed for business and consumer survey expectations that circumvents other filtering methods’ assumptions. Most seasonal adjustment methods are based on a priori assumptions about the structure of the components and do not depend on the features of the specific series. To overcome this limitation, we design a low-pass filter that allows extracting the components with periodicities similar to those that can be found in the dynamics of economic activity. We opt for a Butterworth filter and apply a zero-phase filtering process to preserve the time series’ time alignment. We find that the balances computed with the filtered series are highly correlated with the seasonally-adjusted balances published by the European Commission, albeit the former tend to be smoother for the consumer survey indicators.

Businesses' transaction costs when contracting with governments: the impact of product complexity and public contract management experience

When governments buy products and services, the purchase price reflects not just the seller’s production costs, but also the costs of making the exchange occur. How much selling businesses spend and for which activities has important implications for the management activities governments need to execute to increase the likelihood of a successful exchange. This article develops a framework for analyzing businesses’ transaction cost spending across varying circumstances of selling products to governments. Using unique data from two original surveys of private businesses in Denmark, we provide a rare portrait of how much sellers spend across several categories of contract management activities. Consistent with extant research, we show that these expenditures are lower when selling products with less risky attributes. We also find lower expenditures when businesses have contracted with governments in the past, a finding that suggests that experience can lower the risks of a failed transaction. These results suggest that governments need to calibrate their purchasing activities not only to the circumstances of the exchange, but also to the businesses’ own transaction cost spending.

Robust Estimation for Small Domains in Business Surveys

Abstract Small area (or small domain) estimation is still rarely applied in business statistics, because of challenges arising from the skewness and variability of variables such as turnover. We examine a range of small area estimation methods as the basis for estimating the activity of industries within the retail sector in the Netherlands. We use tax register data and a sampling procedure which replicates the sampling for the retail sector of Statistics Netherlands’ Structural Business Survey as a basis for investigating the properties of small area estimators. In particular, we consider the use of the empirical best linear unbiased predictor (EBLUP) under a random effects model and variations of the EBLUP derived under (a) a random effects model that includes a complex specification for the level 1 variance and (b) a random effects model that is fitted by using the survey weights. Although accounting for the survey weights in estimation is important, the impact of influential data points remains the main challenge in this case. The paper further explores the use of outlier robust estimators in business surveys, in particular a robust version of the EBLUP, M-regression-based synthetic estimators and M-quantile small area estimators. The latter family of small area estimators includes robust projective (without and with survey weights) and robust predictive versions. M-quantile methods have the lowest empirical mean squared error and are substantially better than direct estimators, although there is an open question about how to choose the tuning constant for bias adjustment in practice. The paper makes a further contribution by exploring a doubly robust approach comprising the use of survey weights in conjunction with outlier robust methods in small area estimation.

The Role of Scientific Activities in the Germany`s Chambers of Commerce

The analysis of a model of the German Chambers of Commerce helps to explore the assumption, that along with consulting, expert function (scientific and analytical), viz. collecting of empirical data (business surveys and interviews with entrepreneurs), analytics (preparation of analytical reviews for member firms), expert networking (joint projects with scientific institutions; holding events with the involvement of practicing experts and economic researchers) is one of its key activities. Four main directions are formulated in this area: data collection, interaction with researchers (preparation of analytics), dissemination, and the use of the results on decision-making level (regional/federal government) in order to protect business interests. In conclusion, the author highlights a number of relevant principles for chamber-nets developing in RF and other EAEU countries.

Additionality of government guaranteed loans for SMEs in Israel

The study examines the Israeli Government Loans for SMEs in 2015. Our findings are based on three surveys. A business survey of 384 businesses that were granted a Government loan, a business survey of 99 businesses that were granted loans but decided not to take them and a survey of 50 loan consultants who advised those businesses about their eligibility and the Terms and Conditions of the loans. We tested Loan Adjusted Additionality and Loan Baseline Additionality and found that 53% of loans taken from the Government Loans Foundation (GLF) are additional loans. SMEs would not have taken a loan, or any part of one, if not for the Government Loans Foundation Scheme. Our contribution to the literature is by including Indirect Additionality, demonstrating the importance of the GLF Scheme, not only by assisting SMEs in their financial planning and growth but also, by signalling early stage business resilience, reducing the risks for commercial banks through regulated, financial due diligence. This outcome expands the pool of SMEs which have access to free market loans and has the potential to improve their survival rate, thus fostering economic growth.

Brexit and skill shortages: an empirical analysis of UK SMEs

This paper examines the perspectives of SMEs on Brexit and skill shortages using cross-sectional data of 2,969 SMEs from a UK Government’s Small Business survey for 2016. The logistic regression with clustered standard errors is applied to analyse the association between SMEs considering Brexit as a major business obstacle and the probability of SMEs identifying skill shortages in their businesses. The results show that firms with a shortage of managerial skills/expertise have a 6.5% higher probability to report that Brexit will affect their businesses, followed by difficulties in staff recruitment (4.5%) and shortage of skills within external labour markets (3.8%). Policy recommendations are provided.

Forecasting with Business and Consumer Survey Data

In a context of growing uncertainty caused by the COVID-19 pandemic, the opinion of businesses and consumers about the expected development of the main variables that affect their activity becomes essential for economic forecasting. In this paper, we review the research carried out in this field, placing special emphasis on the recent lines of work focused on the exploitation of the predictive content of economic tendency surveys. The study concludes with an evaluation of the forecasting performance of quarterly unemployment expectations for the euro area, which are obtained by means of machine learning methods. The analysis reveals the potential of new analytical techniques for the analysis of business and consumer surveys for economic forecasting.

Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments

In the context of the Banque de France’s monthly business survey, this document presents the main findings of the textual analysis of business leaders’ comments. First, the richness of these data is illustrated via an elementary sentiment index and the identification of the main social movements since 2009 by means of keywords. Then, the article presents two statistical applications whose reproducibility is discussed. The first one, applied to the 2018 yellow vests and the 2019 strikes, aims to estimate the impact on GDP of an event whose effect is unequivocal. The second, backed by the study of Brexit, aims to characterize, using a supervised learning model and word vectors, the effects of a complex event with multiple impacts.

W-shaped Recovery in the Two Waves of the Coronavirus Pandemic

Our study aims to examine what course the coronavirus crisis took in certain areas, using macroeconomic data and a household and business survey. Our results suggest that the virus has affected different sectors to varying degrees: while some sectors have experienced rapid recovery, others have been characterised by a protracted crisis. The second wave of the coronavirus in the autumn also resulted in a decline in economic data, but to a lesser extent than the first wave in the spring. Overall, the course of the crisis can be considered W-shaped, although some aspects and sectors show a different picture. However, as the viral situation improves, it will be an important task of economic policy to ensure that the last stem of the W is steep, i.e. that the Hungarian economy can return to its previous growth trajectory. To this end, it is essential to lift restrictions, so that household consumption can once again become the engine of growth, and to increase the willingness of companies to invest.

Labor Taxation: Insights from the World Economic Forum Survey

One of the main topics highlighted in the field of economic policy applications is the impact of taxation on labor. In an era in which macroeconomic stability, technological change, and globalization pressure the job market, there exists no strong consensus in the literature on how exactly taxation influences growth, choice between work and leisure, share of income attributed to labor, or participation in different job market segments. This article focuses on employment levels and uses the results of the World Economic Forum (WEF) Executive Opinion Survey (EOS) between 2013 and 2017 to bypass several challenges often faced in the literature. By doing so, we complement the insights of the existing literature by establishing that, in institutionally mature countries, taxation that is deemed by a survey of business executives to pose a disincentive to work reduces employment.

An Integrated Data Framework for Policy Guidance in Times of Dynamic Economic Shocks

Usually, offcial and survey-based statistics guide policy makers in their choice of response instruments to economic crises. However, in an early phase, after a sudden and unforeseen shock has caused incalculable and fast-changing dynamics, data from traditional statistics are only available with non-negligible time delays. This leaves policy makers uncertain about how to most effectively manage their economic countermeasures to support businesses, especially when they need to respond quickly, as in the COVID-19 pandemic. Given this information deficit, we propose a framework that guides policy makers throughout all stages of an unforeseen economic shock by providing timely and reliable data as a basis to make informed decisions. We do so by combining early stage ‘ad hoc’ web analyses, ‘follow-up’ business surveys, and ‘retrospective’ analyses of firm outcomes. A particular focus of our framework is on assessing the early effects of the pandemic, using highly dynamic and largescale data from corporate websites. Most notably, we show that textual references to the coronavirus pandemic published on a large sample of company websites and state-of-the-art text analysis methods allow to capture the heterogeneity of the crisis' effects at a very early stage and entail a leading indication on later movements in firm credit ratings.

Kiet Manufacturing Business Survey Index (BSI) for the 4th Quarter 2020

Kiet Manufacturing Business Survey Index (BSI) for the 4th Quarter 2020

Deciphering Small Business Community Disaster Support using Machine Learning

Small businesses that have demonstrated high levels of pre-disaster local involvement are more likely to take an active role in community resilience during a disaster, regardless of their own financial security. Our investigation of small business survey responses about COVID-19 impacts finds that they are conduits of national support to their local communities. In addition, businesses with natural hazard experience before or during COVID-19 gave to more community groups than hazard inexperienced businesses. While community resilience models often characterize small businesses as passive actors using variables such as employment or financial security, this research suggests that small businesses take an active role in community resilience by providing critical local support. The pandemic presented an opportunity to consider small business’ role in community resilience nationally, which was utilized here to identify the multi-dimensional factors that predict small business operators’ Community Disaster Support. This study improves upon previous research by studying the small business-community resilience interface at both regional (n=197) and national (n=6,121) scales. We predict small business’ active involvement in community resilience using random forest machine learning, and find that adding social capital predictors greatly increases model performance (F-score of 0.88, MCC of 0.67).

KIET Manufacturing Business Survey Index (BSI) for the 3rd Quarter 2021

KIET Manufacturing Business Survey Index (BSI) for the 3rd Quarter 2021

A Study of Supply Chains of Korean Firms in China Based on Business Survey Data

A Study of Supply Chains of Korean Firms in China Based on Business Survey Data

The relationship of economic sentiment and GDP growth in Russia in light of the Covid-19 crisis

Objective: The objective of the article is to prove the empirical and predictive value of the aggregate opinions of businesses and households for expanding cyclical macroeconomic data in Russia, especially during the coronavirus shocks. Research Design & Methods: We use qualitative information from surveys that cover about 24 000 organisations and 5100 households in all Russian regions. The total economic sentiment indicator (TESI) combines information on 18 survey-based indicators. Cross-correlation analysis, Hodrick-Prescott filtering, and a vector autoregressive (VAR) model with dummy variables are used as the research methods. Findings: The study confirms an almost synchronous cyclic conformity of the gross domestic product (GDP) growth and TESI dynamics for the period of 1998-2020. Probable GDP growth until the end of 2021 is estimated based on the expected impulses in the TESI dynamics, including those due to the sudden impact of the coronavirus. Implications & Recommendations: Assessments of business and household activity are reliable and available much earlier than quantitative statistics on GDP growth. Therefore, we advise to use them as an early warning system about economic growth and take them into account in policymaking. Contribution & Value Added: We are the first to confirm the effectiveness and reliability of TESI as a leading indicator of GDP growth in Russia, using data from large-scale business surveys and with a focus on crisis shocks. © 2021, Cracow University of Economics. All rights reserved.

Ansoff’s Strategic Posture Analysis of Small Businesses in Henan Province, China, Post COVID-19

Considering the dynamics of the fast-changing and often unpredictable global environment, a formal, reliable, and comprehensive framework for analyzing a business’ strategic posture may be useful. This paper examines an assessment tool, Igor Ansoff’s seminal contributions to strategic diagnosis. That tool focuses primarily on identifying and enhancing a firm’s strategic financial performance potential through analysis of an industrial sector environmental turbulence level relative to the firm’s aggressiveness and capability responsiveness. A small business survey conducted in the Henan Province of China after the COVID-19 lock-down analyzes the future strategic financial performance potential of the province’s small businesses as well as the interactions among the businesses’ external environmental turbulence level, aggressiveness, and capability responsiveness.