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PROJECT TITLE: Academic Panel Data Collection — ESG Disclosure & Financial Resilience of Firms in Emerging Markets ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DATABASE ACCESS REQUIREMENT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ You MUST have active access to ALL THREE of the following databases to apply: 1. Refinitiv Eikon (LSEG) 2. Bloomberg Terminal 3. Orbis (Bureau van Dijk) Please do not apply if you do not have verified access to all three. When submitting your proposal, confirm which databases you can access and briefly describe your experience extracting academic panel data from each. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PROJECT OVERVIEW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This is a data collection task for an academic research project. The study is confidential and the title will be shared only with the selected freelancer after hiring. The research examines the relationship between ESG and climate-related disclosure and the financial resilience of firms in emerging market economies. The study uses a quantitative panel design covering fiscal years 2013 to 2022. I need a clean, well-structured panel dataset delivered in Excel (.xlsx) format covering all variables listed below. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 1 — FIRM SELECTION CRITERIA ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Firms must meet ALL of the following criteria to be included: 1. FIRM TYPE Small and medium-sized firms defined as: — Total Assets of USD 500 million or below (in any year of the study period), OR — Fewer than 250 employees (where asset data is unavailable) Important: Do NOT pre-filter by size inside the database. Extract all firm sizes and I will apply the threshold during my own analysis. 2. GEOGRAPHY — EMERGING MARKETS ONLY Include firms headquartered in the following countries only: Asia-Pacific: China, India, Indonesia, South Korea, Malaysia, Thailand, Vietnam GCC / MENA: Saudi Arabia, United Arab Emirates, Egypt Africa: South Africa, Nigeria, Kenya Latin America: Brazil, Mexico EMEA: Turkey, Poland Minimum required: at least 10 different countries must be represented in the final dataset 3. ESG DATA AVAILABILITY — MANDATORY FILTER This is the most critical criterion. Every firm included MUST have at least one non-missing value for each of the following: — ESG Score (from Refinitiv Eikon or Bloomberg) — Emissions Score or Carbon Disclosure score — Energy Efficiency Score Firms with no ESG data at all must be excluded before exporting. If applying all three ESG filters returns fewer than 50 firms, remove the Emissions and Energy filters, keep only ESG Score, and message me before exporting. 4. FINANCIAL DATA AVAILABILITY Each firm must have at least 3 consecutive years of non-missing financial data (liquidity or profitability ratios) within the 2013–2022 window. 5. STUDY PERIOD Fiscal years 2013 to 2022 (10 years). Include all available years for each firm — do not drop firms with partial coverage. 6. SECTOR EXCLUSIONS Exclude the following sectors entirely: — Financial Services (banks, insurance companies) — Real Estate Investment Trusts (REITs) All other sectors are eligible. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 2 — VARIABLES REQUIRED ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Extract ALL variables listed below. For time-varying variables, provide annual data for every available year from 2013 to 2022. The preferred source database is shown — use the alternative if the primary source has missing data for a firm. --- A. FIRM IDENTIFIERS (static, one value per firm) --- Variable | Primary Source | Field Name in Database --------------------------|-----------------------|------------------------------- Unique Firm ID / RIC | Refinitiv Eikon | Instrument (RIC) Company Name | Any | Company Name Country of Headquarters | Any | Country of Headquarters ISIN Code | Any | ISIN Code GICS Sector | Refinitiv / Bloomberg | GICS Sector Name Industry Code | Refinitiv Eikon | TRBC Industry Code Date of Incorporation | Orbis / Refinitiv | Date of Incorporation --- B. DEPENDENT VARIABLES — Financial Resilience (annual, 2013–2022) --- Variable | Primary Source | Field Name --------------------------|-----------------------|------------------------------- Current Ratio | Orbis / Refinitiv | Current Ratio Quick Ratio | Orbis / Refinitiv | Quick Ratio Cash Ratio | Orbis / Refinitiv | Cash Ratio Return on Assets (ROA) | Orbis / Refinitiv | Return on Assets (Actual) Return on Equity (ROE) | Orbis / Refinitiv | Return on Equity (Actual) EBIT Margin (%) | Orbis / Refinitiv | EBIT Margin % Interest Coverage Ratio | Orbis / Bloomberg | Interest Coverage Ratio Operating Status | Orbis | Operating Status (Active / Inactive / Dissolved) NOTE on Operating Status: Orbis is the only reliable source for this. Please flag every firm that shows as inactive, dissolved, or insolvent at any point during 2013–2022. --- C. INDEPENDENT VARIABLES — ESG & Climate Disclosure (annual, 2013–2022) --- Variable | Primary Source | Field Name -------------------------------|-----------------------|------------------------------- ESG Score | Refinitiv Eikon | ESG Score ESG Combined Score | Refinitiv Eikon | ESG Combined Score Emissions Score (Carbon) | Refinitiv Eikon | Emissions Score Energy Efficiency Score | Refinitiv Eikon | Policy Energy Efficiency Score Carbon Emissions (tCO2e) | Bloomberg / Refinitiv | Total CO2 Equivalent Emissions CDP Climate Score | Bloomberg | CDP Climate Change Score (if available) --- D. CONTROL VARIABLES — Firm Level (annual, 2013–2022) --- Variable | Primary Source | Field Name -------------------------------|-----------------------|------------------------------- Total Assets (USD) | Orbis / Refinitiv | Total Assets Number of Employees | Orbis / Refinitiv | Employees Average Total Debt to Equity | Orbis / Refinitiv | Total Debt to Common Equity Cash Flow (USD) | Orbis / Refinitiv | Cash Flow Market Capitalisation | Refinitiv / Bloomberg | Market Cap Long Term Growth Rate | Refinitiv | Long Term Growth Mean --- E. CONTROL VARIABLES — Country Level (annual, per country, 2013–2022) --- Variable | Primary Source | Notes -------------------------------|-----------------------|------------------------------- GDP Growth Rate (%) | Refinitiv / Bloomberg | Annual real GDP growth rate Inflation Rate (%) | Refinitiv Eikon | Inflation Rate Period End Climate Policy Statement | Refinitiv Eikon | Climate Policy Statement ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 3 — DELIVERABLE FORMAT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Deliver TWO Excel files: FILE 1 — Wide format (raw database export) One row per firm Separate columns for each variable per year Example: Current_Ratio_2013, Current_Ratio_2014 ... Current_Ratio_2022 File name: Data_Wide_[date].xlsx FILE 2 — Long (panel) format One row per firm per year Columns: firm_id, company_name, country, year, then all variables as single columns File name: Data_Panel_[date].xlsx This is the format required for statistical analysis ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 4 — QUALITY CHECKS BEFORE DELIVERY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Before sending the files, include answers to ALL of the following in your delivery message: Q1. Total number of firms in the dataset? Q2. Total number of firm-year observations (rows in panel format)? Q3. How many firms have a non-missing ESG Score for at least one year? Q4. How many firms have all 3 disclosure variables (ESG + Emissions + Energy) for at least one year? Q5. How many different countries are represented? Q6. What fiscal year range is covered (earliest to latest)? Q7. How many firms have Operating Status data from Orbis? Q8. Which database was used as the primary source for financial variables? MINIMUM THRESHOLDS — do not deliver if any of these are not met: — At least 100 firms total — At least 30 firms with all 3 disclosure variables — At least 10 countries represented — Financial data covering at least 5 years per firm on average If thresholds are not met, message me before delivering and we will adjust the screen together. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 5 — HOW TO APPLY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ In your proposal please include: 1. Confirmation of which databases you have access to 2. Brief description of your experience with academic panel data collection 3. Estimated delivery time 4. Your proposed price Proposals that do not confirm database access will not be considered.
ID Projek: 40317658
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8 pekerja bebas membida secara purata $68 USD untuk pekerjaan ini

Hello, I have over 7 years of experience in Excel, Financial Analysis, Data Collection, and Data Management. I have carefully read the requirements for the Academic Panel Data Collection project related to ESG Disclosure and Financial Resilience of Firms in Emerging Markets. To successfully complete this project, I will utilize my expertise in extracting academic panel data from Refinitiv Eikon, Bloomberg Terminal, and Orbis databases. I will meticulously follow the firm selection criteria, ensuring the inclusion of small and medium-sized firms from specific emerging market countries with mandatory ESG data availability and financial data coverage from 2013 to 2022. I will extract all the required variables, including firm identifiers, dependent variables related to financial resilience, independent variables concerning ESG and climate disclosure, and control variables at both firm and country levels. The deliverables will consist of two Excel files in wide and long formats, meeting all quality checks before final delivery. I am keen to discuss the project further in detail. Please connect with me via chat for a comprehensive discussion. You can visit my Profile at: https://www.freelancer.com/u/HiraMahmood4072 Thank you.
$100 USD dalam 2 hari
6.4
6.4

With robust experience in data analysis and management, I am uniquely poised to undertake this academic research project. As an expert in Excel, I can effectively utilize the mentioned Refinitiv Eikon, Bloomberg Terminal, and Orbis databases for your panel data collection needs. My proficiency with functions, formulas, pivot tables and more will ensure that I deliver a clean and well-structured panel dataset in Excel (.xlsx) format on time. Over the years, I've honed my skills not just in data management but also in providing top-quality service. This means that in addition to meeting your firm selection criteria down to the last detail, I'll be thorough and detail-oriented in my approach to ensure data accuracy. Moreover, my experience with données Financial Services (banks, insurance companies) and Real Estate Investment Trusts (REITs) will allow me quickly exclude these sectors while including all other eligible ones. Lastly, you can count on my dedication to your project's success. From unlimited revisions to ensuring 100% satisfaction at all times, my objective is always a high-quality output that meets the clients' expectations. With 24/7 availability and a commitment to meeting tight deadlines without compromising quality, let me assure you that an immediate and valuable contribution to your project is not only possible but guaranteed when you choose me as the freelancer for this task.
$150 USD dalam 1 hari
4.4
4.4

Hello, I hope you’re having a great day. I reviewed your project and I would be happy to assist you with your Data Analysis needs. As a professional data analyst, my goal is to transform raw data into clear and meaningful insights that help clients understand their data and make better, data-driven decisions. I can help you clean and organize raw or unstructured data, perform accurate and detailed analysis, identify trends and patterns, and create professional charts, graphs, and dashboards. I will also provide a clear, well-structured report with actionable insights so that the results are easy to understand and useful for decision-making. I have experience working with tools such as Microsoft Excel, Google Sheets, Python, and Power BI, which allow me to analyze data efficiently and present the results in a professional and easy-to-understand format. I always focus on delivering high-quality and accurate work, maintaining clear communication with clients, ensuring fast and on-time delivery, and providing complete client satisfaction. I would love to learn more about your project. Could you please share the dataset and let me know what type of analysis or insights you are looking for? Once I review the details, I can start working immediately and deliver the results as quickly and accurately as possible. Thank you for your time and consideration. I look forward to working with you. Best regards,
$30 USD dalam 1 hari
4.3
4.3

Respected Sir, I am Puja Rani. I have read your proposal completely. I have experience I am ready to start working. I am confident that I can handle it easily. If you are interested, please message me and we can discuss further
$30 USD dalam 1 hari
4.4
4.4

Hello there,, I have advanced experience in Data Mining, Statistics, Statistical Analysis and Data Science. With my vast background in data analysis and management, I am confident in my ability to handle your categorical data project effectively and efficiently. I have extensive experience in collecting, cleaning, analyzing, and visualizing data using Python programming, an invaluable asset for a project of this nature. Additionally, I am well-versed with CRISP-DM framework and adept at identifying patterns within datasets Choosing me means benefitting from not only my expertise but also my personal approach to projects. I understand that each task is unique, requiring tailored skills, and so I'm willing to go the extra mile to provide you with results that meet and exceed your expectations. Let's join forces in this project as our combined strengths will surely produce a result that's efficient, elegant and insightful! Let's not waste any more time! Together, we can mine this data efficiently and answer the questions to achieve your goals. Best Regards, Thanks
$30 USD dalam 1 hari
3.4
3.4

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