Growth, Inequality and Poverty: Some Empirical Evidence from Minas Gerais State, Brazil

This chapter is motivated by the fact that the Brazilian economy has one of the highest income inequality index in the world. According to Paes de Barros et al(2000), average income of the 10% richest people in Brazil is 28 times higher than the average income of the 40% poorest people. In Argentina, it is 10 times, 13 times in Costa Rica and 5 times in France. Brazilian growth did not benefit all classes and inequality is increasing since the 60´s. While the 10% richest people get 48% of total income, the 10% poorest people get 0,8% of total income. The inequality problem also arises in the Brazilian regional income analysis. Minas Gerais is a rich and dynamic state with 300.000 km2 divided into 10 different regions, 66 microregions and 853 towns. It is located in the Southeast developed part of the country and is responsible for 10% of Brazilian GDP. As the rest of Brazil, it has a dual economy with prosperity and poverty and social and economic heterogeneity. This chapter empirically analyses the economic growth and income inequality behavior in Minas Gerais towns and microregions from 1970 to 2000, using the income convergence hypothesis. Convergence tests such as Barro and Sala-i-Martin(1992), σ- convergence, Drennan & Lobo(1999) and Quah(1993) are performed. The role of human capital in growth is analysed for Minas Gerais 66 microregions. A comparison is also made between very rich regions and very poor regions of this state to see the relationship between regional inequality and poverty.

Data Mining and Official Statistics: The Past, the Present and the Future

Along with the increasing availability of large databases under the purview of National Statistical Institutes, the application of data mining techniques to official statistics is now a hot topic that is far more important at present than it was ever before. Presented in this article is a thorough review of published work to date on the application of data mining in official statistics, and on identification of the techniques that have been explored. In addition, the importance of data mining to official statistics is flagged and a summary of the challenges that have hindered its development over the course of the last two decades is presented

Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods

Forecasting inflation under varying frequencies

This paper seeks to determine the impact of monthly and annual data frequencies on the accuracy of inflation forecasts attainable via econometric and subspace-based methods. The application considers food inflation across short and long run horizons in Colombia, a country with an inflation targeting regime. The data includes all 54 components of the food consumer price index (CPI) in Colombia from Jan. 1999 Oct. 2012, and the study forecasts the food CPI, and inflation using the parametric and nonparametric techniques of ARIMA, Exponential Smoothing (ETS), Holt-Winters (HW) and Singular Spectrum Analysis (SSA). We �nd that when forecasting the index, ARIMA forecasts are on average best, whilst for monthly inflation forecasting SSA is comparatively better and for annual, the results vary between SSA and ARIMA. These statistically signi�cant �ndings give policy makers an option to select an apt forecasting model which suits their requirements

Risk management, signal processing and econometrics: A new tool for forecasting the risk of disease outbreaks

This paper takes a novel approach for forecasting the risk of disease emergence by combining risk management, signal processing and econometrics to develop a new forecasting approach. We propose quantifying risk using the Value at Risk criterion and then propose a two staged model based on Multivariate Singular Spectrum Analysis and Quantile Regression (MSSA-QR model). The proposed risk measure (PLVaR) and forecasting model (MSSA-QR) is used to forecast the worst cases of waterborne disease outbreaks in 22 European and North American countries based on socio-economic and environmental indica- tors. The results show that the proposed method perfectly forecasts the worst case scenario for less com- mon waterborne diseases whilst the forecasting of more common diseases requires more socio-economic and environmental indicators

Forecasting UK Consumer Price Infation using Infation Forecasts

The inflation rate is a key economic indicator for which forecasters are constantly seeking to improve the accuracy of predictions, so as to enable better macroeconomic decision making. Presented in this paper is a novel approach which seeks to exploit auxiliary information contained within inflation forecasts for developing a new and improved forecast for inflation by modelling with Multivariate Singular Spectrum Analysis (MSSA). Unlike other forecast combination techniques, the key feature of the proposed approach is its use of forecasts, i.e. data into the future, within the modelling process and extracting auxiliary information for generating a new and improved forecast. We consider real data on consumer price inflation in UK, obtained via the Office for National Statistics. A variety of parametric and nonparametric models are then used to generate univariate forecasts of inflation. Thereafter, the best univariate forecast is considered as auxiliary information within the MSSA model alongside historical data for UK consumer price inflation, and a new multivariate forecast is generated. We find compelling evidence which shows the benefits of the proposed approach at generating more accurate medium to long term inflation forecasts for UK in relation to the competing models. Finally, through the discussion, we also consider Google Trends forecasts for inflation within the proposed framework

‘Modelling’ UK tourism demand using fashion retail sales

The United Kingdom (UK) is a world-renowned fashion hub where the economic importance of the tourism sector was recording continuous growth prior to the pandemic. Interestingly, tourism shopping is widely experienced yet seldom discussed from a tourism demand forecasting context. Driven by the potential relevance of tourism shopping and hoping to motivate increased collaboration between the tourism and fashion industries, we analyse whether fashion retail sales can be a leading indicator for inbound tourism demand in the UK. Using the Multivariate Singular Spectrum Analysis leading indicator algorithm, we forecast UK tourism demand and compare the results with six benchmark forecasting models. We find statistically significant evidence for the existence of cross-sector relations between the UK's fashion and tourism industries

Forecasting energy data with a time lag into the future and Google trends

This paper presents a new idea for a forecasting approach which seeks to exploit the information contained within US EIA energy forecasts and related Google trends data for generating a new and improved forecast. The novel forecasting approach can be exploited by using a multivariate system which can consider data with different series lengths and a time lag into the future. Using real historical data, an official forecast for the same variable, and Google Trends search data, we illustrate the possibility of generating a comparatively more accurate forecast for an energy-related variable. The accuracy of the newly generated forecasts are evaluated by comparing with the actual observations and the official forecast itself. We find that the novel forecasting idea cangenerate promising results which call for further in-depth research into developing and improving this multivariate forecasting approach

Fashion MSMEs confronting Climate Change, COVID-19 and Brexit: Key Drivers for Supply Chain Relocation

Purpose This discussion paper presents findings from a research study which analysed the impact of Climate Change, Covid-19 and Brexit on the drivers and factors underlying fashion Micro/Small and Medium Enterprises (MSMEs) supply chain relocation strategies. Methodology The study was based on a mixed methods sequential explanatory research design whereby the quantitative research was followed by the qualitative research. The data collection involved a questionnaire targeting fashion MSMEs in the UK and a focus group with stakeholders. Findings A comprehensive list of factors underlying 16 drivers that could potentially impact the relocation of fashion MSMEs due to Climate Change, Brexit, and Covid-19 was produced. Next, our survey recorded a total of 37 usable responses from UK fashion MSMEs and the ensuing findings were complemented with qualitative insights from 5 stakeholders representing fashion MSMEs. In the report, we identify several factors and drivers underlying relocation strategies differentiated by Climate Change, Brexit, and Covid-19. Finally, through the quantitative and qualitative research, we hone in on 4 focal points for policy intervention: costs, environmental and social sustainability, logistics, and risk management. Policy Implications A key driver underlying relocation strategies for fashion MSMEs in the UK is cost. Given the importance of MSMEs for the UK economy and local communities, the government could curb relocations by helping MSMEs with the costs of doing business via subsidies, fiscal policy reforms, lenient trade policies, and improvements in efficiency and productivity of government services (e.g., border controls), which would also help overcome factors associated with logistics as a driver underlying relocation strategies. In terms of tackling environmental and social sustainability, facilitating the development of stakeholder networks capable of performing sustainability practices within SMEs and stricter regulation along with rewards in the form of subsidies for compliance would help curb relocations. Finally, in terms of curbing concerns around risk management as a driver underlying relocation strategies, the government could focus on policy interventions that would minimise the risks of doing business in the UK and make provisions for dedicated programmes tailored to improve fashion MSMEs risk management capabilities. It should be noted that for these policy initiatives to be effective, the industry should also proactively engage in complementary activities that would reinforce government interventions

Designing And Validating The Methodology For The Internet Assessment Of Fish Consumption At A University Setting

Assessing fish consumption is complex and involves several factors; however, the use of questionnaires in surveys and the use of the Internet as tool to collect data have been considered promising approaches. Therefore, the objective of this research was to design a data collection technique using a questionnaire to assess fish consumption by making it available on a specific home page on the Internet. A bibliographical survey or review was carried out to identify the features of the instrument, and therefore pre-tests were conducted with previous instruments, followed by the Focus Group technique. Specialists then performed an analysis and conducted an online pre-test. Multivariate data analysis was applied using the SmartPLS software. The results indicate that 1.966 participants belonging to the University of São Paulo (USP) community participated in the test, and after the exclusion of some variables, a statistically significant results were obtained. The final constructs comprised consumption, quality, and general characteristics. The instrument consisted of behavioral statements in a 5-point Likert scale and multiple-choice questions. The Cronbach's alpha reliability coefficient was 0.66 for general characteristics, 0.98 for quality, and 0.91 for consumption, which indicate good reliability of the instrument. In conclusion, the results proved that the Internet assessment is efficient. The instrument of analysis allowed us to better understand the process of buying and consuming fish in the country, and it can be used as base for further research.342315323Bargas-Avila, J.A., Lotscher, J., Orsini, S., Opwis, K., Intranet satisfaction questionnaire: Development and validation of a questionnaire to measure user satisfaction with the Intranet (2009) Computers In Human Behavior, 25 (6), pp. 1241-1250. , http://dx.doi.org/10.1016/j.chb.2009.05.014Batagelj, Z., Vehovar, V., Technical and methodological issues in surveys (1998) Proceedings of the 53° Annual Conference of the American Association For Public Opinion Research (AAPOR), , http://www.ris.org/ris98/stlouis, St. Louis. Retrieved fromBliven, B., Kaufman, S., Spertus, J.A., Electronic collection of health-related quality of life data: Validity, time, benefits and patient preference (2001) Quality Life Research, 10 (1), pp. 15-22. , http://dx.doi.org/10.1023/A:1016740312904Boeckner, L., Pullen, S.C.H., Walker, S.N., Abbott, G.W., Block, T., Use and realiability of Word Wide Web Version of the block health habits and history questionnaire with older rural women (2002) Journal of Nutrition Education and Behavior, 34, pp. S20-S24. , http://dx.doi.org/10.1016/S1499-4046(06)60307-2Cantrell, M.A., Lupinacci, P., Methodological issues in online data collection (2007) Journal of Advanced Nursing, 60 (5), pp. 544-549. , http://dx.doi.org/10.1111/j.1365-2648.2007.04448.xChang, L., Krosnick, J.A., Comparing oral interviewing with self-administered computerized questionnaires an experiment (2010) Public Opinion Quarterly, 74 (1), pp. 154-167. , http://dx.doi.org/10.1093/poq/nfp090Chin, W.W., The partial least squares approach to structural equation modeling (1998) Modern Methods For Business Research, pp. 295-336. , In G. A. Marcoulides (Ed.), Mahwah: Lawrence Erlbaum AssociatesCronk, B.C., West, J.L., Personality research on the Internet: A comparison of web based and traditional instruments in take-home and in-class settings (2002) Behavior Research Methods Instruments and Computers, 34 (2), pp. 177-180. , http://dx.doi.org/10.3758/BF03195440Falk, R.F., Miller, N.B., (1992) A Primer For Soft Modeling, , New York: Akron Presshttp://www.brasilfoodtrends.com.br/Brasil_Food_Trends/index.html, Federação das Industrias do Estado de São Paulo-FIESP. (2010), Brasil food trends, São Paulo: FIESP. Retrieved fromFerri, P., Cavalli, N., Costa, E., Mangiatordi, A., Mizzella, S., Pozzali, A., Scenini, F., Italian university students and digital technologies: Some results from a field research (2009) Communications In Computer and Information Science, 49 (3), pp. 357-365. , http://dx.doi.org/10.1007/978-3-642-04757-2_38(2009) The State of World Fisheries and Aquaculture (SOFIA), , Food and Agriculture Organization of the United Nations-FAO, Rome: FAOGefen, D., Straub, D.W., Boudreau, M.C., Structural equation modeling and regression: Guidelines for research practice (2009) Communications of the Association For Information Systems, 4 (1), pp. 1-77Hair Jr., J.F., Black, W.C., Babin, B.J., Anderson, R.E., Tatham, R.L., (2009) Análise Multivariada De Dados, , 6. ed.). Porto Alegre: BookmanHanning, R.M.D., Royall, J.E., Toews, L., Blashill, L., Wegener, J., Driezen, P., Web-based food behaviour questionnaire: Validation with grades six to eight students (2009) Canadian Journal of Dietetic Practice and Research, 70, pp. 172-178. , http://dx.doi.org/10.3148/70.4.2009.172Hanscom, B., Lurie, J.D., Homa, K., Weinstein, J., Computerized questionnaires and the quality of survey data (2002) Spine, 27 (6), pp. 1797-1801. , http://dx.doi.org/10.1097/00007632-200208150-00020Hershberger, S.L., Marcoulides, G.A., Parramore, M.M., Structural equation modeling: An introduction (2003) Structural Equation Modeling: Applications In Ecological and Evolutionary Biology, , http://dx.doi.org/10.1017/CBO9780511542138.002, In B. H. Pugesek, A. Tomer & A. V. Eye (Eds.), Cambridge: Cambridge University PressKlem, L., Structural equation modeling (2006) Reading and Understanding More Multivariate Statistics, pp. 227-260. , In L. G. Grimm & P. R. Yarnold (Eds.), Washington: American Psychological AssociationMalhotra, N., (2008) Pesquisa De Marketing: Uma Orientação Aplicada, , 5. ed.). Porto Alegre: BookmanMaruayama, G.M., (1998) Basic of Structural Equation Modeling, , Thousand Oaks: Sage PublicationsMatthys, C., Pynaert, I., de Keyzer, W., Henauw, S., Validity and reproducibility of an adolescent Web-based food frequency questionnaire (2007) Journal of the American Dietetic Association, 107 (4), pp. 605-610. , http://dx.doi.org/10.1016/j.jada.2007.01.005Mina, K., Fritschi, L., Knuiman, M., A valid semiquantitative food frequency questionnaire to measure fish consumption (2007) European Journal of Clinical Nutrition, 61, pp. 1023-1031. , http://dx.doi.org/10.1038/sj.ejcn.1602617Morgan, D., (1997) Focus Group As Qualitative Research, pp. 80-88. , London: Sage Publications. Qualitative Research Methods Series 16Mueller, R.O., Structural equation modeling: Back to basics (1997) Structural Equation Modeling, 4 (4), pp. 353-369. , http://dx.doi.org/10.1080/10705519709540081Oetterer, M., (2002) Industrialização Do Pescado Cultivado, , Guaíba: AgropecuáriaPasquali, L., (2003) Psicometria: Teoria Dos Testes Na Psicologia E Na Educação, , Petrópolis: VozesPerez, G., Zwicker, R., Fatores determinantes da adoção de sistemas de informação na área de saúde: Um estudo sobre o prontuário médico eletrônico (2010) Revista De Administração Mackenzie, 11 (1), pp. 174-200. , http://dx.doi.org/10.1590/S1678-69712010000100008Ribeiro, R.C.L., Panato, E., Silva, M.M.S., Rosado, L.E.F., Rosado, G.P., Validade relativa de um questionário de freqüência alimentar para utilização em adultos (2009) Revista De Nutrição, 22 (1), pp. 81-95. , http://dx.doi.org/10.1590/S1415-52732009000100008Rodrigues, D.S., Ramos, R.A.R., Mendes, J.F.G., A system to evaluate and monitor quality of life in a University Campus (2005) Proceedings of the 9th International Conference On Computers In Urban Planning and Urban Management (CUPUM), , http://repositorium.sdum.uminho.pt/bitstream/1822/5064/1/Rodrigues_CI_1_2005.pdf, London. Retrieved fromSantos, F.V., (2001) A Importância Da Atividade Física Na Qualidade De Vida Disseminada Numa Página Da Internet (Dissertação De Mestrado), , Universidade Federal de Santa Catarina, FlorianópolisSirot, V., Dumas, C., Leblanc, J.C., Margarit, I., Food and nutrient intakes of French frequent seafood consumers with regard to fish consumption recommendations: Results from the CALIPSO study (2011) British Journal of Nutrition, 105 (9), pp. 1369-1380. , http://dx.doi.org/10.1017/S0007114510005027Sonoda, D.Y., (2006) Demanda Por Pescado No Brasil Entre 2002 E 2003, , Tese de doutorado). Universidade de São Paulo, PiracicabaSoriano, J.M., Molto, J.C., Manes, J., Dietary intake and food pattern among university students (2000) Nutrition Research, 20 (9), pp. 1249-1258. , http://dx.doi.org/10.1016/S0271-5317(00)00217-7Stanton, J.M., Rogelberg, S.G., Using Internet/intranet web pages to collect organizational research data (2001) Organizational Research Methods, 4 (3), pp. 200-217. , http://dx.doi.org/10.1177/109442810143002Touvier, M., Kesse-Guyot, E., Méjean, C., Pollet, C., Malon, A., Castetbon, K., Hercberg, S., Comparison between an interactive web-based self-administered 24 h dietary record and an interview by a dietitian for large-scale epidemiological studies (2001) British Journal of Nutrition, 105 (7), pp. 1055-1064. , http://dx.doi.org/10.1017/S0007114510004617Trondsen, T., Scholderer, J., Lund, E., Lund, E., Eggen, A., Perceived barriers to consumption of fish among Norwegian women (2003) Appetite, 41 (3), pp. 301-314. , http://dx.doi.org/10.1016/S0195-6663(03)00108-9(2010) Anuário Estatístico, , http://sistemas3.usp.br/anuario, Universidade de São Paulo-USP, Brasil: USP. Retrieved fromVanderslice, J., Laflamme, D.M., Wynkoop-Simmons, K., Comparing fish consumption information collected via a telephone survey and a food frequency questionnaire (2008) Epidemiology, 19 (6), pp. S315Veiga, L., Gondim, S.M.G., A utilização de métodos qualitativos na ciência política e no marketing político (2001) Opinião Pública, 2 (1), pp. 1-15Vinholis, M.M.B., Azevedo, P.F., Segurança do alimento e rastreabilidade: O caso BSE (2002) RAE Eletrônica, 1 (2), pp. 1-19. , http://dx.doi.org/10.1590/S1676-56482002000200008Zwicker, R., Souza, C.A., Bido, D.S., (2008) Uma Revisão Do Modelo Do Grau De Informatização De Empresas: Novas Propostas De Estimação E Modelagem Usando PLS (Partial Least Squares), , In Anais do 32° Encontro da ANPAD, Rio de Janeiro. CD-RO