Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile
Abstract
:1. Introduction
2. World Context: COVID-19
3. Citizen Perception and Local Economic Development
4. Methodology
4.1. Data and Method
4.2. Study Area
5. Results
5.1. Descriptive Analysis
- The first instrument was applied to individuals; besides economic categories, it surveyed specifics related to the coronavirus context, such as sources of information for the citizenry in the face of the pandemic, assessment of national and regional media, importance of social networks, and emotions during quarantine.
- The second instrument was aimed at companies and surveyed the general background information of their owners as to the national and regional economy, employment, and investment. In addition, it included categories such as those directly related to the health emergency situation and assessment of crisis management by national and regional authorities.
5.2. Multinomial Logistic Regression
6. Discussion and Conclusions
Author Contributions
Funding
Conflicts of Interest
References and note
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Questions | Variable | Alternatives | n | Marginal Percentage |
---|---|---|---|---|
How prepared is the country to face the pandemic? | Country preparedness | Well-prepared | 12 | 3.8% |
Moderately prepared | 160 | 51.1% | ||
Not at all prepared | 141 | 45.0% | ||
What is your sex? | Sex | Female | 177 | 56.5% |
Male | 135 | 43.1% | ||
Prefer not to say | 1 | 0.3% | ||
How old are you? | Age | 18–25 years | 63 | 20.1% |
26–33 years | 46 | 14.7% | ||
34–40 years | 60 | 19.2% | ||
41–50 years | 74 | 23.6% | ||
51–60 years | 47 | 15.0% | ||
61 years or more | 23 | 7.3% | ||
What is your educational attainment? | Education | Elementary | 1 | 0.3% |
High school | 96 | 30.7% | ||
Technical | 40 | 12.8% | ||
University | 46 | 14.7% | ||
Postgraduate studies | 130 | 41.5% | ||
What do you expect regarding household income in the next 12 months? | Projected income | Will increase | 28 | 8.9% |
Will remain the same | 94 | 30.0% | ||
Will decrease | 146 | 46.6% | ||
Does not know | 45 | 14.4% | ||
What is your household debt situation? | Household debt | Complicated | 72 | 23.0% |
Moderately complicated | 122 | 39.0% | ||
Without problems | 105 | 33.5% | ||
Does not know/Does not respond | 14 | 4.5% | ||
Has your household had any supply problems? | Supplies | Yes | 64 | 20.4% |
No | 246 | 78.6% | ||
Does not know/Does not respond | 3 | 1.0% | ||
What is your political persuasion? | Political persuasion | Left | 16 | 5.1% |
1 | 11 | 3.5% | ||
2 | 12 | 3.8% | ||
3 | 14 | 4.5% | ||
4 | 8 | 2.6% | ||
Center | 21 | 6.7% | ||
6 | 6 | 1.9% | ||
7 | 7 | 2.2% | ||
8 | 3 | 1.0% | ||
Right | 5 | 1.6% | ||
I have no political persuasion | 166 | 53.0% | ||
Does not know/Does not respond | 44 | 14.1% | ||
How do you evaluate the performance of the Chilean government in the face of the pandemic? | Evaluation national government for pandemic | Very bad | 68 | 21.7% |
Bad | 70 | 22.4% | ||
Fair | 103 | 32.9% | ||
Good | 58 | 18.5% | ||
Very good | 14 | 4.5% | ||
How do you evaluate the performance of the regional government in the face of the pandemic? | Evaluation regional government for pandemic | Very bad | 58 | 18.5% |
Bad | 70 | 22.4% | ||
Fair | 118 | 37.7% | ||
Good | 56 | 17.9% | ||
Very good | 11 | 3.5% | ||
How prepared are you financially to face the pandemic? | Financial preparedness for pandemic | Very bad | 60 | 19.2% |
Bad | 77 | 24.6% | ||
Fair | 129 | 41.2% | ||
Good | 47 | 15.0% | ||
Will the company where you work be able to financially withstand the pandemic and not go bankrupt? | Company in the face of the pandemic | Yes | 108 | 34.5% |
No | 43 | 13.7% | ||
Does not know | 162 | 51.8% | ||
What is the level of fear of losing your job? | Fear of losing job | High | 133 | 42.5% |
Moderate | 100 | 31.9% | ||
Low | 80 | 25.6% | ||
How do you evaluate the work of the national media in dealing with the pandemic? | National media | Very bad, generate panic | 102 | 32.6% |
Bad | 47 | 15.0% | ||
Fair | 107 | 34.2% | ||
Good | 40 | 12.8% | ||
Very good, keep people informed | 17 | 5.4% | ||
How do you evaluate the work of the regional media in dealing with the pandemic? | Regional media | Very bad, generate panic | 43 | 13.7% |
Bad | 53 | 16.9% | ||
Fair | 125 | 39.9% | ||
Good | 67 | 21.4% | ||
Very good, keep people informed | 25 | 8.0% | ||
What were the social networks that provided you with the most relevant information to make decisions or take measures about the coronavirus? | Social networks for pandemic | 115 | 36.7% | |
49 | 15.7% | |||
38 | 12.1% | |||
34 | 10.9% | |||
YouTube | 11 | 3.5% | ||
None | 66 | 21.1% |
Observed | Predicted | |||
---|---|---|---|---|
Well-Prepared | Moderately Prepared | Not at All Prepared | Percent Correct | |
Well-prepared | 12 | 0 | 0 | 100.0% |
Moderately prepared | 0 | 142 | 18 | 88.8% |
Not at all prepared | 0 | 17 | 124 | 87.9% |
Overall percentage | 3.8% | 50.8% | 45.4% | 88.8% |
Effect | Model Fitting Criteria | Likelihood Ratio Tests | ||
---|---|---|---|---|
−2 Log Likelihood of Reduced Model | Chi-Squared | Degrees of Freedom | p-Value | |
Intercept | 199.969 | 0.000 | 0 | – |
Sex | 370.670 | 170.701 | 4 | 0.000 |
Age | 2721.641 | 2521.672 | 10 | 0.000 |
Education | 385.351 | 185.382 | 8 | 0.000 |
Income projection | 951.248 | 751.278 | 6 | 0.000 |
Household debt | 457.733 | 257.764 | 6 | 0.000 |
Supplies | 204.003 | 4.034 | 4 | 0.401 |
Political persuasion | 216.214 | 16.245 | 22 | 0.804 |
Evaluation national government for pandemic | 250.876 | 50.907 | 8 | 0.000 |
Evaluation regional government for pandemic | 632.366 | 432.397 | 8 | 0.000 |
Financial preparedness for pandemic | 376.776 | 176.806 | 6 | 0.000 |
Company in the face of pandemic | 209.906 | 9.937 | 4 | 0.042 |
Fear of losing job | 204.415 | 4.446 | 4 | 0.349 |
National media | 423.152 | 223.183 | 8 | 0.000 |
Regional media | 416.013 | 216.044 | 8 | 0.000 |
Social networks for pandemic | 566.052 | 366.083 | 10 | 0.000 |
Questions | Variable | Alternatives | n | Marginal Percentage |
---|---|---|---|---|
In your opinion, the economic situation of the country in one year will be: | Economic projection for the country | Worse than it is now | 27 | 52.9% |
Same as it is now | 6 | 11.8% | ||
Better than it is now | 18 | 35.3% | ||
What is the sex of the owner? | Sex | Male | 41 | 80.4% |
Female | 8 | 15.7% | ||
Prefer not to say | 2 | 3.9% | ||
What do you think of the policies developed by the Chilean government to support businesses? | Policies to support businesses | Very bad | 7 | 13.7% |
Bad | 8 | 15.7% | ||
Fair | 15 | 29.4% | ||
Good | 19 | 37.3% | ||
Very good | 2 | 3.9% | ||
The debt situation of your company before the pandemic was? | Pre-pandemic debt | Complicated | 5 | 9.8% |
Moderately complicated | 17 | 33.3% | ||
Without problems | 29 | 56.9% | ||
What do you think will be the debt situation of your company after the pandemic? | Post-pandemic debt | Complicated | 27 | 52.9% |
Moderately complicated | 19 | 37.3% | ||
Without problems | 5 | 9.8% | ||
To support companies, the government should consider privileging national over international companies | Policy privileges for national companies | Not selected | 34 | 66.7% |
Selected | 17 | 33.3% | ||
Which state economic stakeholders give you the most guarantees or confidence to deal with the economic crisis resulting from the social upheaval and COVID-19? | Confidence in economic stakeholders | Ministry of Revenue | 28 | 54.9% |
Ministry of Economy | 5 | 9.8% | ||
SERNAC: National Consumer Service | 2 | 3.9% | ||
Central Bank | 12 | 23.5% | ||
Superintendencies | 1 | 2.0% | ||
SEREMIs: Regional Ministerial Secretariats | 3 | 5.9% | ||
Do you think that the creation of the Ñuble Region provides better prospects for dealing with future global pandemics or disasters in a decentralized manner? | Regional perspectives | No | 21 | 41.2% |
Yes | 30 | 58.8% |
Observed | Predicted | |||
---|---|---|---|---|
Worse than It Is Now | Same as It Is Now | Better than It Is Now | Percent Correct | |
Worse than it is now | 25 | 1 | 1 | 92.6% |
Same as it is now | 0 | 6 | 0 | 100.0% |
Better than it is now | 1 | 0 | 17 | 94.4% |
Overall percentage | 51.0% | 13.7% | 35.3% | 94.1% |
Effect | Model Fitting Criteria | Likelihood Ratio Tests | ||
---|---|---|---|---|
−2 Log Likelihood of Reduced Model | Chi-Squared | Degrees of Freedom | p-Value | |
Intercept | 4.500 | 0.000 | 0 | – |
Sex | 18.962 | 14.463 | 4 | 0.006 |
Policies to support businesses | 65.362 | 60.862 | 8 | 0.000 |
Pre-pandemic debt | 38.162 | 33.663 | 4 | 0.000 |
Post-pandemic debt | 38.890 | 34.390 | 4 | 0.000 |
Policy privileges for national companies | 13.725 | 9.225 | 2 | 0.010 |
Confidence in economic stakeholders | 64.045 | 59.545 | 10 | 0.000 |
Regional perspectives | 13.398 | 8.898 | 2 | 0.012 |
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Umaña-Hermosilla, B.; de la Fuente-Mella, H.; Elórtegui-Gómez, C.; Fonseca-Fuentes, M. Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile. Sustainability 2020, 12, 9553. https://doi.org/10.3390/su12229553
Umaña-Hermosilla B, de la Fuente-Mella H, Elórtegui-Gómez C, Fonseca-Fuentes M. Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile. Sustainability. 2020; 12(22):9553. https://doi.org/10.3390/su12229553
Chicago/Turabian StyleUmaña-Hermosilla, Benito, Hanns de la Fuente-Mella, Claudio Elórtegui-Gómez, and Marisela Fonseca-Fuentes. 2020. "Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile" Sustainability 12, no. 22: 9553. https://doi.org/10.3390/su12229553
APA StyleUmaña-Hermosilla, B., de la Fuente-Mella, H., Elórtegui-Gómez, C., & Fonseca-Fuentes, M. (2020). Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile. Sustainability, 12(22), 9553. https://doi.org/10.3390/su12229553