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ENG Student, Malcolm Wong, Publishes on Malaysiakini

Updated: Dec 18, 2022


Malcolm Wong

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Jun Xiang, a first-year student of XMUM English Language and Literature Department publishes in Malaysiakini, an online news portal which advocates professional and ethical journalism.

Entitled “Add more specifics to the inflation figures, please”, this paper takes issue with the government's general reporting of inflation rates by analyzing the intuitive experience of price variation in life and data provided in authoritative documents. The author advocates that tackling inflation needs transparency.




Malcolm shares his thoughts about conducting the research.


“Oh great, prices have shot up like every other store.” I shared this thought with everyone whenever we realised that it now costs more for the same meal, or lesser portions with the same price.


Inflation was hitting every shelf I went to: in the mamak stalls, roti canai and nasi goreng cost 50 cents, sometimes 1 Ringgit more. In bread, a 3 Ringgit loaf of bread now costs 30 cents more. The same plate of spaghetti costs RM5 more, with a much lesser portion for me to be nourished.


A quick calculation of the price hikes estimated the inflation I experienced around 10 to 20 percent. Yet when i checked the official statistics of inflation, the current inflation rate is at 3.4 percent, as reported by the Department of Statistics Malaysia (DOSM).


Gradually I realised: the figures we see in economic indicators and documents may not often accurately represent our daily ongoings.



Data is collected and quantified within a small area within a huge sample field, and the sum total becomes the aggregate representation of all which the method of measurement is often neglected when revealing data to the common folk. Economic indicators are meant to be calculated to reflect the whole situation of the economy in general terms rather than specific conditions.


Yet figures are not omniscient nor a complete transparent mirror of reality - data measurements are calculated and programmed by humans alone. Within the methods we used to make sense of the data will inevitably have loopholes due to human bias, error or judgement.


The problem remains then - how reliable can data be to accurately represent reality? The statistics measured what is already present - it is relatively easy to quantify the total barrels of oil produced and the amount of chicken in farms, but it remains a heavily disputed area to quantify the measurements of happiness or standard of living for example, - for although however objective in figures they may be, the definition of happiness or a good life varies with individuals.



Going back to the question of actual inflation, not everyone participates in every sector of the economy and inflation in certain areas will severely affect and increase the cost of living. Since food and beverages are among the highest price hikes, the actual inflation experienced by the common people will be much higher, compared to what is reported of the 3.4% inflation.


We are used to making decisions and determining outcomes with the assistance of numbers, and gradually become reliant on figures. Statistics gives us security, a quantification method to make sense and grasp a situation in an increasingly complicated world of social phenomena and the digitalisation of social activities online.


Blindly assuming the credibility of statistics without given specifics is a major flaw in accessing and responding to shown data, making significant errors when used as an aid to make important economic or business decisions.



Nevertheless, compiled statistics can still be a reliable indicator - provided the data measurements are openly accounted for with acknowledgement for errors.


I had hoped by submitting my ideas for publication many more would reconsider and critically view the way we rely on figures as an absolutely correct method for decision making, especially among administrators and scholars in academia to develop accurate reporting while taking into account certain flaws in data measurement.


 
 
 

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