Decent Work and Economic Growth
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Spaghetti Pataas: Inflation Rates of Certain Commodities in the Philippines
With the subtle but steady increase in the inflation rate every year, it is no wonder that many people are left wondering how they will adapt. The graph shows the inflation rate of significant commodity groups every month from 1995 to 2023. Namely, 'All Items', 'Housing, Water, Electricity Gas, and Other Fuels,' 'Information and Communication,' 'Food and Non-Alcoholic Beverages,' 'Transport,' and 'Alcoholic Beverages and Tobacco.' Negative inflation rates are indicated by a darker shade of the line color when coming below the 0 axis.
Diving deeper into the plot, each line shows the differences in the inflation rate and how each group has its own fluctuations, ranging from subtle changes to very dramatic increases or decreases in the rate. Out of all the commodity groups shown, Alcoholic Beverages and Tobacco have the most fluctuations with a drastic change per year, indicating the effects of laws and policies on the price.
On the other hand, the graph of Information and Communication has significant fluctuations around the year 2000, indicating the significant developments in technology during that time, but gradually slows down and eventually stagnates with little fluctuations.
Although the All Items commodity group seems to be on the lower end of the spectrum in terms of the inflation rate, this shows how the overall inflation rate, which is based on All Items, is balanced out despite the dramatic change in rates of some commodity groups.
IO-n na nga: Correlation Spotted Between Agriculture and Other Industries
As the data points show, there seems to be a correlation between the input from the agricultural industry to the different industries in a country and the output of those industries.
Of note is the Food, beverages, and tobacco industry with its clear linear correlation and relatively large industry size in each country. Another large industry in Indonesia's case is Construction with also a clear correlation. These first impressions on the data points lead to curiosity on which industries have a strong correlation from the agriculture input.
Rising Rice Prices: Analyzing Price Movements of Agricultural Commodities
The graph illustrates the months wherein rice, and other goods, are experiencing above average prices. It also categorizes these goods into four.
The first category, which is colored blue, corresponds to seafood. The second category, colored purple, is for fruits, vegetables, and other rootcrops. The third, depicted with color pink, is for meat products. The last category, which is colored with yellow, is for grains and starches.
Fueled Up: CPI of Transportation Rises Amidst Fluctuating Fuel Prices
The plot depicts the Consumer Price Index for Philippine Land Transportation and Fuel from January 2019 to December 2023. Each solid line represents different land transportation groups, while each dashed line represents either gasoline or diesel.
The plot tells us that the CPI of land transportation in the Philippines has been trending upwards alongside fuel prices, which may be caused by a multitude of societal factors over the past five years.
Comparing Cost of Living and Wages Across the Philippines
The plot illustrates the poverty threshold (shown in dashed lines) and minimum wage (shown in solid lines) between the National Capital Region (NCR) and the rest of the Philippines from around 2003 onwards. For this plot, we used the poverty threshold as our metric for cost of living. Poverty threshold is defined by the PSA as the monthly minimum income required for a family to meet the basic food and non-food requirements. The x-axis represents the date, while the y-axis represents the price of the minimum wage/poverty threshold in Philippine pesos (PHP). Minimum wage is at a daily rate, while poverty threshold is at a monthly rate, so the poverty threshold was divided by 30 to make it daily. The average of the poverty thresholds of the non-NCR regions was taken and used to determine the poverty threshold for the rest of the Philippines.
The plot shows the disparity of cost of living and wages between the NCR and the rest of the country. Minimum wage in the non-NCR regions is lower than the NCR minimum wage by around 100 to 200 pesos for the last 20 years. Conversely, the poverty threshold of the NCR is lower than that of the non-NCR regions by 100 pesos. This shows that Metro Manila, being the economic center of the country, can offer higher wages and cheaper goods.
The plot also shows that wages are not keeping up with cost of living. In fact, the gap between cost of living and minimum wage, both in the NCR and outside of it, has been steadily increasing in the last 20 years. This is shown by how the regression lines for the poverty threshold are slightly steeper than the regression lines for minimum wage. This shows that despite a rise in minimum wages, Filipinos living off of minimum wage still cannot afford to meet basic food and non-food requirements.
Through the Reddit Lens of Filipino Workers
The dataset was clustered into five (5) topics as extracted by LDA using t-SNE. In the resulting plot, each color represents a topic cluster. These clusters are made up of points where each corresponds to a post; the larger the radius of the point, the greater the engagements a post has accumulated.
Topic 3, identified as Job Application and the focus of our hypothesis, lagged as third in both the number of posts and engagements. Topic 2, identified as BPO Work & Culture, placed first for the total number of engagements, while Topic 5, identified as Employee Well-being, placed first for the total number of posts. Topic 1, identified as Employee Exit Process, placed last for both categories.
Moreover, we can see how each topic is grouped and how close they are. For instance, Workplace Management is relatively separate from Employee Exit Process, which could mean employees quit for reasons other than workplace management. BPO Work & Culture is closely related to Workplace Management and Job Application but relatively isolated from the others. This may be because BPO is a leading industry. Job Application dabbles with the others but ties closely with Employee Exit Process since an exit from a job usually means applying for another one. Employee Well-being interacts with all other clusters and has a small patch in the middle of the plot, which could indicate that it is a core concern of most posts.
Effect of SHS and COVID-19 on the Philippine Unemployment Rate
In analyzing the trends of the unemployment rate in the Philippines per quarter since 2016, four significant events can have an impact on the Philippine unemployment rate. The implementation of Senior High School (SHS) in the second quarter of 2016, the graduation of the first batch of SHS students in the second quarter of 2018, the COVID-19 pandemic which triggered a nationwide lockdown in the first quarter of 2020, and the establishment of the new normal in the first quarter of 2022 - according to the Department of Education.
As shown in the graph, the trends show a notable increase in the unemployment rate in the quarters where these four significant events have taken place.
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| Title | Project by | |
|---|---|---|
Spaghetti Pataas: Inflation Rates of Certain Commodities in the Philippines | ** D.M. Dee, D.R. Dy, J.M. Lozada | |
IO-n na nga: Correlation Spotted Between Agriculture and Other Industries | Flask E. Aldemita II, A.J. Marcel, N.M. Valdez | |
Rising Rice Prices: Analyzing Price Movements of Agricultural Commodities | Group Two J.C. Gaza, R.E. Roy, C.J. Salces | |
Fueled Up: CPI of Transportation Rises Amidst Fluctuating Fuel Prices | JJD D.E. Montenejo, J.V. Pascual, J.C. Toledo | |
Comparing Cost of Living and Wages Across the Philippines | JuJuBee B.M. Amurao, L.J. Maca, J.C. Yabut | |
Through the Reddit Lens of Filipino Workers | pocarí A.M. Domondon, S.M. Eliserio, R.K. Mañago | |
Effect of SHS and COVID-19 on the Philippine Unemployment Rate | Ternary N. Feliciano, P.H. Quijano, T.N. Reyes | |