Finance and Firm Volatility: Evidence from Small Business Lending in China

2021 ◽  
Author(s):  
Tao Chen ◽  
Yi Huang ◽  
Chen Lin ◽  
Zixia Sheng
Keyword(s):  
Causal Effect ◽  
Fuzzy Regression ◽  
Data Set ◽  
Credit Access ◽  
Credit Score ◽  
Score Threshold ◽  
Online Trading ◽  
Exit Probability ◽  
Fuzzy Regression Discontinuity Design ◽  
Alternative Sources

The online trading platform Alibaba provides financial technology (FinTech) credit for millions of micro, small, and medium-sized enterprises (MSMEs). Using a novel data set of daily sales and an internal credit score threshold that governs the allocation of credit, we apply a fuzzy regression discontinuity design (RDD) to explore the causal effect of credit access on firm volatility. We find that credit access significantly reduces firm sales volatility and that the effect is stronger for firms with fewer alternative sources of financing. We further look at firm exit probability and find that firms with access to FinTech credit are less likely to go bankrupt or exit the business in the future. Additional channel tests reveal that firms with FinTech credit invest more in advertising and product/sector diversification, particularly during business downturns, which serves as effective mechanisms through which credit access reduces firm volatility. Overall, our findings contribute to a better understanding of the role of FinTech credit in MSMEs. This paper was accepted by Haoxiang Zhu, finance.

scholarly journals Flags and anthems: naturalisation effects on income and employment

2017 ◽  
Vol 44 (4) ◽  
pp. 491-504
Author(s):  
Jan-Jan Soon
Keyword(s):  
Causal Effect ◽  
Threshold Value ◽  
Fuzzy Regression ◽  
Host Countries ◽  
Market Outcomes ◽  
Data Set ◽  
Content Type ◽  
Difficult Time ◽  
European Values ◽  
Fuzzy Regression Discontinuity Design

Purpose Even though Europe has recently undergone a difficult time and is recovering from the aftermath of prevalent unemployment, immigrants are still flocking towards Europe and taking up citizenships of their host countries through naturalisation. The purpose of this paper is to look at the how naturalised immigrants fare in terms of income and employment chances, compared to immigrants. Design/methodology/approach Using a fuzzy regression discontinuity design and the 2008 European Values Study integrated data set with a final sample of 4,460 observations, this paper isolates the causal effect of naturalisation on the income and employment chances of immigrants by exploiting exogenous variations generated by the eligibility rules for naturalisation in 41 European countries. Findings Main findings show that the probability of being naturalised increases for eligible immigrants, income and employment chances increase for eligible immigrants, and income and employment chances increase for naturalised immigrants. Research limitations/implications This study has a data limitation, where in using the discontinuity design, there is an unbalanced number of observations to the left and right of the design’s threshold value. Originality/value There are limited studies using causal models or potential outcome frameworks to examine the effect of immigrant naturalisation on labour market outcomes in Europe. This study fills this gap.

scholarly journals Regional Transfer Multipliers

2018 ◽  
Vol 86 (5) ◽  
pp. 1901-1934 ◽  
Author(s):  
Raphael Corbi ◽  
Elias Papaioannou ◽  
Paolo Surico
Keyword(s):  
Regression Discontinuity ◽  
Causal Effect ◽  
Public Spending ◽  
Fuzzy Regression ◽  
Regression Discontinuity Design ◽  
Allocation Mechanism ◽  
Municipal Governments ◽  
Local Labour ◽  
Income Multiplier ◽  
Fuzzy Regression Discontinuity Design

Abstract A series of discontinuities in the allocation mechanism of federal transfers to municipal governments in Brazil allow us to identify the causal effect of public spending on local labour markets, using a “fuzzy” Regression Discontinuity Design (RDD). Our estimates imply a cost per job of about 8,000 US dollars per year and a local income multiplier around two. The effect comes mostly from employment in services and is more pronounced among less financially developed municipalities.

Eviction and Voter Turnout: The Political Consequences of Housing Instability

2021 ◽  
pp. 003232922110507
Author(s):  
Gillian Slee ◽  
Matthew Desmond
Keyword(s):  
Voter Turnout ◽  
Causal Effect ◽  
Additive Model ◽  
The United States ◽  
Data Set ◽  
Endogeneity Bias ◽  
Political Consequences ◽  
Housing Costs ◽  
Election Results ◽  
The Impact

In recent years, housing costs have outpaced incomes in the United States, resulting in millions of eviction filings each year. Yet no study has examined the link between eviction and voting. Drawing on a novel data set that combines tens of millions of eviction and voting records, this article finds that residential eviction rates negatively impacted voter turnout during the 2016 presidential election. Results from a generalized additive model show eviction’s effect on voter turnout to be strongest in neighborhoods with relatively low rates of displacement. To address endogeneity bias and estimate the causal effect of eviction on voting, the analysis treats commercial evictions as an instrument for residential evictions, finding that increases in neighborhood eviction rates led to substantial declines in voter turnout. This study demonstrates that the impact of eviction reverberates far beyond housing loss, affecting democratic participation.

Household consumption and home production at retirement in Thailand: evidence from a regression discontinuity approach

2022 ◽  
pp. 1-25
Author(s):  
Sasiwooth Wongmonta
Keyword(s):  
Low Income ◽  
Regression Discontinuity ◽  
Household Consumption ◽  
Fuzzy Regression ◽  
Household Expenditure ◽  
Home Production ◽  
Work Related ◽  
Home Work ◽  
Time Use Survey ◽  
Fuzzy Regression Discontinuity Design

Abstract This paper uses Socio-Economic Surveys covering the period from 2013 to 2019 and the 2015 Time Use Survey to investigate the extent to which household consumption changes at retirement in Thailand. A fuzzy regression discontinuity design is applied to evaluate the retirement effect on total household expenditure and expenditures on four major categories: food-at-home, work-related items, non-durable entertainment, and others. The results reveal that retirement decreases household expenditure by 11%. Further investigations show that the dramatic declines in expenditures on work-related and non-durable entertainment contribute significantly to the spending drop at retirement. The magnitudes of the declines are more pronounced for low-income and low-wealth households. The results also indicate that the retirees spend more leisure time on home production activities after retirement. Once accounting for this effect, it finds that the drop in total household expenditure decreases to 6%. These results suggest that the sizable consumption expenditure drop at retirement is due to substituting away from market purchased goods toward home-produced goods.

scholarly journals The Impact of Teachers Unions on Teachers’ Well-Being Under Various Legal Institutions: Evidence From District–Teacher Matched Data

AERA Open ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 233285841986729 ◽  
Author(s):  
Eunice S. Han
Keyword(s):  
Multilevel Models ◽  
Causal Effect ◽  
Well Being ◽  
Legal Environment ◽  
Legal Institutions ◽  
Data Set ◽  
Teachers Unions ◽  
The Difference ◽  
Matched Data ◽  
The Impact

This article examines how teachers unions affect teachers’ well-being under various legal institutions. Using a district–teacher matched data set, this study identifies the union effects by three approaches. First, I contrast teacher outcomes across different state laws toward unions. Second, I compare the union–nonunion differentials within the same legal environment, using multilevel models and propensity score matching. Finally, unexpected legal changes restricting the collective bargaining of teachers in four states form a natural experiment, allowing me to use the difference-in-difference estimation to identify the causal effect of weakening unionism on teacher outcomes. I find that (a) many teachers join unions even when bargaining is rarely or never available, and meet-and-confer or union membership rate affects teachers’ lives in the absence of a bargaining contract; (b) how unions influence teacher outcomes vary greatly by different legal environment; and (c) the changes in public policy limiting teachers’ bargaining rights significantly decrease teacher compensation.

scholarly journals Cryptocurrencies: They´re really that lucrative?

2021 ◽  
Vol 129 ◽  
pp. 03002
Author(s):  
Roman Blazek
Keyword(s):  
Value Added ◽  
Investment Activity ◽  
Advantages And Disadvantages ◽  
Digital Currency ◽  
Virtual Economy ◽  
Online Trading ◽  
Digital Money ◽  
Basic Purpose ◽  
Alternative Sources ◽  
Analyze Data

Research background: Cryptocurrency is a digital currency that is intended for online trading. It uses and implements the principles of cryptography to create a distributed, decentralized and secure digital currency. Virtual money is a new and promising branch of the virtual economy that brings many advantages and disadvantages in a global sense. Many people have become involved in cryptocurrency hype because high investments in this digital money have been seized during the pandemic. The rise in revenues from this digital money has gripped the world globally. Purpose of the article: The basic purpose and chosen goal is to analyze the use of cryptomen trading during the global Covid-19 pandemic, as well as investing in these alternative sources of investment, which are gaining more attention every day precisely because of their freedom and detachment. Methods: The article will analyze data that will be compared based on the years before the Covid-19 pandemic and during the Covid-19 pandemic. Based on these data, the investment activity of people, companies, corporations is compared. Findings & Value added: Based on the results in the article, it was found that during the Covid-19 pandemic, the interest in investing in cryptocurrencies increased compared to the interest in investing in cryptocurrencies before the pandemic. The overall result is that people are moving to a new way of holding money, as cryptocurrencies are a new way to the future, as banks are unable to provide such returns from client deposits as cryptocurrencies, but they are associated with much greater risk.

The Impact of US Monetary Growth on Bitcoin Trading Volume in the Current Economic Uncertainty

2020 ◽  
pp. 493-509
Author(s):  
İsmail Canöz
Keyword(s):  
Causal Relationship ◽  
Trading Volume ◽  
Causal Effect ◽  
Study Data ◽  
Time Interval ◽  
Time Varying ◽  
Economic Uncertainty ◽  
Causality Test ◽  
Data Set ◽  
The Impact

This study examines the effect of US monetary growth on Bitcoin trading volume. To achieve this purpose, firstly, the symmetric causality test is used. Following this test, another symmetric causality test is used to reveal a time-varying causal effect between variables. The data set covers the period from July 2010 to July 2019. The results of the first symmetric causality test, which considers the time interval of the study data as a whole, show that there is no causal relationship between variables. According to the results of the second causality test, these support the previous results substantially. However, an interesting detail is the causal relationship between variables for the period between April 2019 and July 2019. The reason for this relationship could be that investors who are indecisive during the current economic uncertainty add Bitcoin to their portfolios in response to the Federal Reserve's decisions.

scholarly journals Doubly Robust Estimation of Causal Effect

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Xiaochun Li ◽  
Changyu Shen
Keyword(s):  
Propensity Score ◽  
Causal Effect ◽  
Model Specification ◽  
Robust Estimator ◽  
Data Set ◽  
Multiple Regressions ◽  
Doubly Robust Estimation ◽  
Doubly Robust ◽  
Confounding Adjustment ◽  
The Relationship

Propensity score–based methods or multiple regressions of the outcome are often used for confounding adjustment in analysis of observational studies. In either approach, a model is needed: A model describing the relationship between the treatment assignment and covariates in the propensity score–based method or a model for the outcome and covariates in the multiple regressions. The 2 models are usually unknown to the investigators and must be estimated. The correct model specification, therefore, is essential for the validity of the final causal estimate. We describe in this article a doubly robust estimator which combines both models propitiously to offer analysts 2 chances for obtaining a valid causal estimate and demonstrate its use through a data set from the Lindner Center Study.

scholarly journals Who Are the Beneficiaries of China’s New Rural Pension Scheme? Sons, Daughters, or Parents?

2019 ◽  
Vol 16 (17) ◽  
pp. 3159
Author(s):  
Zhang ◽  
Luo ◽  
Robinson
Keyword(s):  
Psychological Health ◽  
Well Being ◽  
The Elderly ◽  
Fuzzy Regression ◽  
Pension Scheme ◽  
Adult Daughters ◽  
Adult Sons ◽  
Pension Income ◽  
Fuzzy Regression Discontinuity Design ◽  
Using Data

y applying a fuzzy regression discontinuity design, this study investigates whether sons, daughters, or parents are the beneficiaries of China’s New Rural Pension Scheme. Using data drawn from the China Health and Retirement Longitudinal Survey, our results indicate that pension income crowds out approximately 27.9% of the monetary support from adult sons and decreases the likelihood that adult sons live with their parents by 6.5%. However, we do not find a significant effect of pension income on the likelihood that adult daughters live with their parents. In regards to the well-being of parents, which is measured by consumption and health outcomes, the results show that pension income increases food and non-food consumption by 16.3 and 15.1%, respectively, and improves the psychological health of the elderly. Accounting for the different effects of pension income for those with different income levels, our results show that the New Rural Pension Scheme only has a significant effect on the poor elderly.

Estimating the causal effects of treatment

2002 ◽  
Vol 11 (3) ◽  
pp. 206-215 ◽  
Author(s):  
Graham Dunn
Keyword(s):  
Causal Effect ◽  
Randomised Trial ◽  
Outcome Data ◽  
Causal Effects ◽  
Estimation Methods ◽  
Random Allocation ◽  
Statistical Research ◽  
Data Set ◽  
The One ◽  
Randomised Controlled

SUMMARYObjective – To provide a relatively non-technical review of recent statistical research on the analysis and interpretation of the results of randomised controlled trials in which there are possibly all three of the following types of protocol violation: non-adherence to allocated treatment, contamination (that is, patients receiving treatments other than the one to which they were allocated) and attrition (missing outcome data). Methods – The estimation methods involve the use of potential outcomes (counterfactuals) in the definition of a causal effect of treatment and in drawing valid inferences concerning its size. Results – The methods are explained through the use of simple arithmetical expressions involving the counts from three-way contingency tables (Outcome by Treatment Received by Random Allocation). Illustration is provided through the use of a hypothetical data set. Conclusions – Recent advances in statistical methodology enable one to estimate treatment effects from the results of randomised trials in which the treatment actually received is not necessarily the one to which the patient was allocated. These methods allow one to make adjustments to allow for both non-compliance and loss to follow-up. Even for such a 'broken' randomised trial, inference concerning causal effects is safer than that from data arising from an observational study that never involved random allocation in the first place.

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