Policy Chat over Curry Noodles
Good morrning. No Parliament today, so I am in my office to catch up with the rest of the officers and interns. I will give a lecture and take them to lunch. Since this budget session started I have not been to the office, except once two weeks ago. I will be getting an update on our Bulan Kebajikan and also research by interns.
I also dropped by to consume my favourite neighbourhood curry noodle at Teik Kee. I had a long chat with a few of my constituents over breakfast. The topics of gripe are GST, 1MDB, and durians that nobody can afford to eat any more. In this posting I am gonna talk about durians.
Musang King prices have dropped recently to around RM50/kilo but consumer sentiment has turned off completely when it hit RM125/kilo. The overall negative consumer sentiment has yet to recover since. In addition to being too expensive there is also an overwhelming feeling that we are getting second grade durians and that the best are exported to Singapore, HK and China. This kind of consumer resentment coupled by yoyo pricing is causing unhappiness to both producers and consumers.
What can we do as a policy to ensure fair durian prices and to stop the yoyo pricing? If we leave it to “free market” no Malaysians will be able to afford to eat durians. To make any policy work, we need to first gather accurate big data. In fact a lot of data; from total production volume, locality of old and new farms, seasonal pricing, to domestic and international consumption patterns. We also need to understand and keep up with changes in the industry. For instance, the widespread use of instant freezing technology can impact the supply of durians, hence its pricing too.
What we then need to do is to match supply and local demand, and by adjusting export tarriff of durians, the government can discourage or encourage the exports of durian. This will ensure that Malaysians can at least afford to taste our national fruit. By deploying this simple mechanism and testing it over a period of one to two years, we can then create a predictive model for optimal results that benefit both producers and consumers.