bank of thailand ’ s monetary policy : navigating towards sustained growth veerathai santiprabhob, governor of the bank of thailand thailand focus 2018 august 29, 2018 ladies and gentlemen, it is my pleasure to be addressing you this morning. i will take this opportunity to speak to you about thailand ’ s economic outlook and monetary policy at this important time. but before i move on, i would like to first thank the stock exchange of thailand for hosting this event, and all participants for your interest in the thai economy and the thai capital market. this is an important time, not only for the global economy, but also for the thai economy. after five years of sub - par growth rates, thailand has managed to restore economic growth to its potential. as the economy moves from a recovery phase towards an expansionary phase, the role of macroeconomic policy needs to evolve accordingly. what used to be a stimulative tool will eventually have to transition into a support on which the economy could grow on a sustainable basis. furthermore, we need to step up structural reform policy to address long - term challenges. ladies and gentlemen, the turning point of macroeconomic policy stance is not a straightforward one. imagine yourself on a road trip with a group of friends. you were driving, and one of your friends asked you, “ when will we make a turn? ” if you have a gps navigator or open up google maps, you might be able to say with precision, “ in 2. 5 kilometers. ” when talking about a policy course, the answer might be, “ in the next two or three quarters, if things go according to plan. ” in real life, we policymakers do not have the luxury of having a gps navigator, not to mention the fact that this said turn could be moved closer or further away without giving any warnings in this volatile world. what we do have, however, are indicators we observe from our surroundings, and indicators of road conditions and possible storms ahead of us. similarly, the mpc considers a number of factors when formulating a policy decision — not only the current state of such factors, but also their longer - run trends and expectations of risk scenarios going forward. for a small open economy in an increasingly volatile world, mpc ’ s decisions will have to be data dependent. in my address to you this morning, i will share with you the factors that the mpc considers when making policy decisions. since the main objective of a flexible

also have been about 1 / 4 percentage point higher as well, implying that measurement issues of this sort likely account for only part of the productivity slowdown in current statistics. research in this area is at an early stage, but this example illustrates the depth of analysis supporting our data - dependent decisionmaking. how tight is the labor market? let me now turn from the measurement issues raised by the information age to an issue that has long been at the center of monetary policymaking : how tight is the labor market? answering this question is central to our outlook for both of our dual - mandate goals of maximum employment and price stability. while this topic is always front and in the case of facebook, brynjolfsson, collis, and eggers ( 2019 ) found that the median user required compensation of $ 48 to live without that social media platform for a month. byrne and corrado ( 2019 ). - 8center in our thinking, i am raising it today to illustrate how we are using big data to inform policymaking. until recently, the official data showed job gains over the year through march 2019 of about 210, 000 a month, which is far higher than necessary to absorb new entrants into the labor force and thus hold the unemployment rate constant. in august, the bls publicly previewed the benchmark data revision coming in february 2020, and the news was that job gains over this period were more like 170, 000 per month — a meaningfully lower number that itself remains subject to revision. the pace of job gains is hard to pin down in real time largely because of the dynamism of our economy : many new businesses open and others close every month, creating some jobs and ending others, and definitive data on this turnover arrive with a substantial lag. thus, initial data are, in part, sophisticated guesses based on what is known as the birth – death model of firms. several years ago, we began a collaboration with the payroll processing firm adp to construct a measure of payroll employment from their data set, which covers about 20 percent of the nation ’ s private workforce and is available to us with a roughly oneweek delay. 15 as described in a recent research paper, we constructed a measure that provides an independent read on payroll employment that complements the official statistics. 16 while experience is still limited with the new measure, we find promising evidence that it can refine our real - time picture of job gains. for example, in the first eight months