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Firm-Level Finance & Panel Econometrics2016–2024 confirmatory panel · Completed FE study

Short-Horizon Claim Concentration and Operating Efficiency

Poster summary

Stata 17 · reghdfe · panel diagnostics · multiple testing · System GMM audit

A completed firm-panel study of whether a greater current-liability share predicts subsequent asset turnover, profitability, and operating cash generation.

01

Research question

Does short-horizon claim concentration predict future operating efficiency within Vietnamese listed firms?

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Methodology

Dynamic firm fixed effects with clustered inference, prespecified robustness models, reverse-direction tests, multiple-testing correction, and System GMM diagnostics

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Dataset

9,144 observations across 1,405 nonfinancial Vietnamese listed firms in the main 2016–2024 specification

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Main finding

Lagged short-horizon claim concentration is positively associated with future asset turnover (0.1011, p=0.0385), but the p25-to-p75 magnitude is 0.023 outcome standard deviations and significance varies across robustness models.

Short-Horizon Claim Concentration and Operating Efficiency

Overview

This project evaluates whether the share of current liabilities in total liabilities predicts subsequent operating efficiency. The final decision is to retain the fixed-effects evidence and reject the invalid GMM specifications.

Research Question

Does short-horizon claim concentration predict future asset turnover and related operating outcomes within Vietnamese listed firms?

Economic or Technical Motivation

A larger share of near-term claims may impose settlement pressure that disciplines asset use, but it may also reflect financial fragility or reverse selection. The design tests prediction within firms without assigning a causal mechanism.

Data

The source panel covers 2010–2024. The confirmatory sample uses nonfinancial firms during 2016–2024; the main model contains 9,144 observations and 1,405 firms. Short-horizon claim concentration is current liabilities divided by total liabilities, not a short-term debt ratio.

Methodology

The pipeline uses dynamic firm fixed effects with clustered standard errors, prespecified alternative outcomes and samples, reverse-direction models, COVID sensitivity, multiple-testing correction, and System GMM diagnostics.

Main Findings

Lagged claim concentration is positively associated with future asset turnover: 0.1011 with SE 0.0488 and p=0.0385. A p25-to-p75 shift corresponds to 0.0281 asset-turnover units, or 0.023 outcome standard deviations. Secondary ROA and CFO/assets estimates are positive before family-wise correction.

Robustness, Validation, or Model Assessment

The main sign is retained in all comparable robustness models, while 56% have p-values below 0.05. Raw-outcome, rank, and COVID-excluded variants are less precise. All System GMM variants fail required diagnostics; those estimates are rejected rather than used as confirmation.

Tools and Technologies

Stata 17, reghdfe, firm fixed effects, clustered inference, panel diagnostics, Holm and Benjamini–Hochberg adjustments, and System GMM auditing are directly demonstrated.

Limitations

The effect is small, statistical significance is not uniform across transformations, and reverse selection is not ruled out. Dynamic fixed effects may be biased in a short panel, while the attempted GMM remedy fails its diagnostics.

Deliverables

  • Reproducible modular Stata pipeline
  • Validation gates and source-version audit
  • CSV/RTF result tables and diagnostic files
  • Final results report and decision memo