The Impact of the Capture of Leaders of Criminal Organizations on the Labor Market: Evidence from Mexico

This paper estimates the impact of the capture of leaders of criminal organizations on the labor market in municipalities where these organizations operated between 2004 and 2006. The difference-in-difference analysis compares different employment outcomes in cartel locations and the rest, before and after the capture of cartel leaders. The results show that captures caused a decrease in nominal wages and paid employment in cartel municipalities. Using Economic Census Data, I find that captures also caused a fall in the number of establishments and had a negative impact on other establishment outcomes. This document focuses exclusively on the impact of the capture of leaders of criminal organizations on the labor market until 2011 without studying other possible consequences, and thus does not make an integral assessment of this policy

Collaborative governance in increasing the competitiveness of Micro Small Medium Enterprises (MSMEs) through the Jakpreneur program

Based on the 2016 Economic Census, the number of businesses in DKI Jakarta has reached more than one million businesses, or 98.78%. The potential of MSMEs is able to reduce the unemployment rate and can drive the wheels of the Indonesian economy and DKI Jakarta specifically. However, in the current conditions, MSMEs in DKI Jakarta still have many limitations in terms of management and empowerment. Therefore, the DKI Jakarta Provincial Government created the JakPreneur Program to help MSMEs advance to class to be competitive and maintain their business. The DKI Jakarta Provincial Government embraces stakeholders to collaborate in developing the JakPreneur Program. The purpose of this study is to describe precisely the process and form of collaboration through the approach of collaborative governance in the JakPreneur Program and provide recommendations for program improvement. This study used a post-positivist approach with a qualitative method through interviews and literature study. The results of this study indicate that the collaboration process takes place effectively between the relevant stakeholders. The collaboration formed in this context is represented by implementing a number of activities from the P1-P7 stages of the JakPreneur program.

When workers matter most: a study of worker cooperatives and the prioritization of workers through COVID-19

PurposeAs a part of the authors’ continued efforts to understand the experience and trends related to small business cooperatives, the US Federation of Worker Cooperatives (USFWC) and the Democracy at Work Institute (DAWI) explored themes around the impact of the COVID-19 pandemic on worker cooperatives and democratic workplaces.Design/methodology/approachThe USFWC and DAWI conduct a biannual Economic Census of worker cooperatives and democratic workplaces. Survey themes this year included questions around the impact of the COVID-19 pandemic on individual firms.FindingsGeneral findings indicate that worker cooperatives experienced financial losses similar to conventional small businesses, but that this varied widely by industry. Although it has been found that BIPOC-owned conventional small businesses have been some of the hardest hit during the pandemic, the authors find that there may be some mitigating protective effects of the worker cooperative form when the authors explore the impacts on worker cooperatives with a majority BIPOC workforce. Additionally, the authors find that worker cooperatives and democratic workplaces strive to ensure the safety and wellbeing of their workers even when facing significant financial challenges throughout the pandemic.Research limitations/implicationsThis research utilizes non-random convenience sampling in data collection. The outreach for our biannual Economic Census is concentrated on a highly connected worker cooperative and democratic workplace network, the experiences of which may not generalize to the larger worker cooperative and democratic workplace landscape. Additionally, outreach efforts were hindered by challenges presented by the pandemic that were not present in prior census years, as was firm bandwidth to respond, which likely affected the sample composition in comparison to prior years.Originality/valueWorker cooperatives have been proven to be a resilient crisis response form of business, but little is known about how the worker cooperative ecosystem in the United States is faring in the face of the continuing COVID-19 crisis.

SOCIAL MEDIA MARKETING: PROSPECTS AND OPPORTUNITIES FOR SMALL AND MEDIUM ENTERPRISES

This paper aims to explore prospects and opportunities of the use of Social Media Marketing tools by Small & Medium Enterprises (SMEs) in Pakistan, to develop and promote their business. The research data findings postulate the fact that the SMEs constitute over 90 percent of 3.2 million business enterprises listed under the Economic Census of Pakistan (2005,) generate 25 percent of manufacturing export earnings and contribute 30 percent to the annual GDP in the country. Despite this fact, the SMEs are considered to be less formally organized sector of the economy relative to large enterprises, have limited access to financial resources and are limited to their scale of production. Social Media Marketing, on the other hand, operates on a less complex organizational structure, requires lower financial investments and even makes an organization appear to be larger than its actual size. These analogous attributes establish a correlation between SMEs and Social Media Marketing. This paper intends to identify the various possibilities which can contribute to the growth and development of the SME sector in Pakistan. The study examines the data evidence and empirically tests the correlation between SME business progress & social media as a mode of business promotion. Consequently, this research paper focuses on how small businesses can use Social Media not only for advertising and marketing their products and services but also for building the business overall, employing transactional mechanisms, sharing information with customers and receiving their feedback and recommendations on a regular basis.

Applying Machine Learning for Automatic Product Categorization

Every five years, the U.S. Census Bureau conducts the Economic Census, the official count of US businesses and the most extensive collection of data related to business activity. Businesses, policymakers, governments and communities use Economic Census data for economic development, business decisions, and strategic planning. The Economic Census provides key inputs for economic measures such as the Gross Domestic Product and the Producer Price Index. The Economic Census requires businesses to fill out a lengthy questionnaire, including an extended section about the goods and services provided by the business. To address the challenges of high respondent burden and low survey response rates, we devised a strategy to automatically classify goods and services based on product information provided by the business. We asked several businesses to provide a spreadsheet containing Universal Product Codes and associated text descriptions for the products they sell. We then used natural language processing to classify the products according to the North American Product Classification System. This novel strategy classified text with very high accuracy rates - our best algorithms surpassed over 90%.

Female Workers and Heads of Households in Buenos Aires Countryside During the Nineteenth Century (San Vicente, Buenos Aires, Argentina, 1815–1895)

Rural Buenos Aires, as many other regions of what constitutes Argentina today, underwent some radical transformations during the course of the nineteenth century. We here study San Vicente, a rural area where micro-family households were predominant, in order to explore two complementary aspects of the changing social environment. First, the possibilities women had of being the heads of households as well as the resources available to them to earn their living by different means. Secondly, how their position in society evolved during this period. Our main sources are data gathered from the register of inhabitants of 1815 and the National Population Censuses of 1869 and 1895, which we will complement with data from the economic census carried out in 1895. We will see that when competition intensified, there came to be fewer opportunities for women to head households or businesses.

PELATIHAN PEMASARAN ONLINE PUSAT INKUBATOR WIRAUSAHA DAN KLINIK UMKM KOTA CILEGON

Small and Micro Enterprises (SMEs) has an important role in supporting the Indonesian economy. On the other hand, the internet has developed rapidly. This internet media progress can be utilized by SMEs to develop their business. However, in Indonesia, the number and presentation of MSEs that have used digital media is still very low. The use of the internet for the business world is can be seen in the product marketing process, for example the increasing online business in Indonesia, including in Banten, and is applied to all business activities. However, the use of the internet in SMEs in Banten is still very small. According to the 2016 Economic Census, only around 37 thousand businesses or 3.84 percent use the internet both for product marketing processes and others and only around 2.55 percent of the internet is used for marketing, this fact become the basis for training and strengthening for the community, especially for SMEs in Banten to realize how important it is to become "internet literate" and encourage the use of the internet for marketing even higher.

Prospect Prediction Model Of Indonesian Telematics Medium Large Size Enterprises Using Deep Learning Approach

Analysis of business prospects is an important part of predicting a country's economic conditions. Currently, the prediction of prospects for medium-big sized enterprises (MLE) in the telematics sector has not been widely researched and represented as a factor of economic development in Indonesia. In fact, in accordance with the development of the Industrial Revolution 4.0, the telematics sector business is one of the pillars that is a priority to be developed in Indonesia. The main purpose of this study is to construct the prediction model for prospects in the Indonesian telematics LME sector using a deep learning approach. We used data from the 2016 National Economic Census as many as 2500 preprocessed data. The deep learning approach in this study used a multilayer perceptrón (MLP) architecture, 17 attributes, 3 hidden layers and 5 target classes. The attributes in question include province, business owner education, legal entity status, length of operation, business network, total assets, business lava, number of workers, difficulties, partnerships, marketing innovations, comparison of profit with the previous year, and development plans. The target class of prospects are excellent, good, neutral, bad and very bad. The optimal results were achieved in epoch 50 conditions with a learning reate of 0.2 and an accuracy rate of 98.80%. Based on the prediction model, this business prospect can be used as a reference for the development of MLE in the telematics sector in Indonesia. This prospect model still lacks visualization and attribute analysis that affects the classification of prospects for Indonesian telematics MLE. Research development opportunities can be carried out through the integration of the whitebox model in the deep learning model and complementing a web-based graphical user interface (GUI) to make it easier for stakeholders to develop strategies based on the strength of attributes that affect the prospects for MLE Telematics Indonesia. This is expected to boost the competitiveness of the prospects for Indonesian telematics MLE.

Robust Estimation for a Generalised Ratio Model

It is known that data such as business sales and household income need data transformation prior to regression estimate as the data has a homoscedastic error. However, data transformations make the estimation of mean and total unstable. Therefore, the ratio model is often used for imputation in the field of official statistics to avoid the problem. Our study aims to robustify the estimator following the ratio model by means of M-estimation. Reformulation of the conventional ratio model with homoscedastic quasi-error term provides quasi-residuals which can be used as a measure of outlyingness as same as a linear regression model. A generalisation of the model, which accommodates varied error terms with different heteroscedasticity, is also proposed. Functions for robustified estimators of the generalised ratio model are implemented by the iterative re-weighted least squares algorithm in R environment and illustrated using random datasets. Monte Carlo simulation confirms accuracy of the proposed estimators, as well as their computational efficiency. A comparison of the scale parameters between the average absolute deviation (AAD) and median absolute deviation (MAD) is made regarding Tukey's biweight function. The results with Huber's weight function are also provided for reference. The proposed robust estimator of the generalised ratio model is used for imputation of major corporate accounting items of the 2016 Economic Census for Business Activity in Japan.

Income Inequality and Socioeconomic Segregation in Jakarta

Socioeconomic segregation has become a common phenomenon, both in the Global North and Global South, and highly relates to income inequality. The merging of these two notions affects the geography of residential areas which are based on the socio-occupational composition. This chapter focuses on the Jakarta Metropolitan Area (JMA). Not only is Jakarta the largest metropolitan area in Southeast Asia, it is also one of the most dynamic. Batavia, the colonial capital of the former Dutch East Indies in the first half of the twentieth century, was a small urban area of approximately 150,000 residents. In the second half of the century, Batavia became Jakarta, a megacity of 31 million people and the capital of independent Indonesia was beset with most of the same urban problems experienced in twenty-first-century Southeast Asia, including poverty, income inequality, and socioeconomic segregation. This study aims to identify the correlation among income inequality, socioeconomic segregation, and other institutional and contextual factors which caused residential segregation in JMA. The analysis consists of two stages. First, we examine income inequality measured by the Gini Index as well as the occupational structure based on the International Standard Classification of Occupations (ISCO). Second, we investigate residential segregation by using the Dissimilarity Index as a result of socioeconomic intermixing in residential areas. The data in this study comes from multiple sources including Indonesia’s Central Bureau of Statistics, Indonesia’s National Socio-economic Survey (Susenas), Indonesia’s Economic Census, Jakarta’s Regional Bureau of Statistics, and policies related to the housing system and investment in the JMA. This study also produces maps of socioeconomic segregation patterns from several sources including Jakarta’s Geospatial Information Centre, Jakarta’s Spatial Plan Information System, and the Indonesian Poverty Map by the SMERU Research Institute.