|Adjustments||Not Seasonally Adjusted|
|Source||Instituto Nacional de Estadística Geografia e Informática (INEGI)|
|Release||Monthly Survey of Business Opinion|
|Industrial Production||Dec 2019||101.36||101.66||Index 2013=100, SA||Monthly|
|Change in Inventories||2019 Q3||158,276||119,720||Mil. MXN, SAAR||Quarterly|
|Real Change in Inventories||2019 Q3||128,307||87,207||Mil. 2013 MXN, SAAR||Quarterly|
|Business Confidence||Mar 2019||51.41||50.87||Dif. Index=50,NSA||Monthly|
For Mexico, a survey-based producer confidence indicator reported by INEGI. Monthly from 2004.
The national economic situation changes increasingly dynamic and frequent, which means that the statistical information generated should be commensurate with the speed of them, and so adequately support the decisions to be taken by various information users. Under this premise developed the Monthly Survey of Business Opinion (Encuesta Mensual de Opinión Empresarial, EMOE), which generates monthly indicators which allows to establish the status and expectations of the manufacturing sector based on the views of business leaders from the selected economic units.
The source writes:
The overall objective of the survey is to generate monthly composite indicators that track qualitative character, manufacturing orders, and trend of economic activity. This allows an advance in their behavior and serve as support in decision-making for the public and private sectors. The information captured by the EMOE is referred to very long periods defined or determined and variables related to the tendency of the activity economic and manufacturing orders are referenced a historical period (comparison month benchmark against the previous month) and to a period estimates (Comparative month after month against reference). Confidence indicators are captured relating the current time against the twelve months and twelve previous post. The question of exchange rate expectations refers to the last day of the interview and the last day of December. As regards inflation expectations question, it concerns the accumulated from January to the month of the interview and the throughout the year (January to December).
The population under study are manufacturing firms the country with more than 100 persons employed. The population framework consists of the directory Economic Census 2004. The directory with 4,427 companies, representing 65.0% of staff occupied and 86.0% of total revenues in the manufacturing sector. The sampling is stratified probabilistic selection randomly and independently in each stratum. This includes with certainty in the sample firms with 1.000 and more employees. The units of selection have a known probability and distinct ground up to be selected. The primary units of the sample with similar characteristics are grouped to form strata.
Companies in the population are classified under four sizes based on the staff: 101 to 250 employees, 251 to 500 employees, 501 to 1000 employees, and 1001 or more employees. The sample is distributed proportionally to the size of stratum, except for stratum 1, in which the criterion inclusion is for sure. To calculate the size of the sample, using the expression to estimate the total working population with Neyman affixation, including with certainty in the sample, the 397 companies in stratum 1. Considering the 95% relative error 4%, non-response rate of 20%, design effect of 0.96 and producer confidence index of 49.64%, we obtained a sample size of 119 companies together with certain companies, giving a total of 511.
The producer confidence Indicator is created based on the percentage of answer the following six questions, related on the economic situation and business:
There are five response options. The last four questions, however, for first two, only three: "Yes", "No" and "Do not know." The option "Do not know" is not considered for calculating the indicator, which was distributed proportionally between the other two options (between "Yes" and "No") which are arranged at the ends.
The percentage response of each of the five alternatives (much more, greater, equal, lower and much smaller) are weighted to each of the variables: sales, assets fixed or employed personnel. Also, information refers to the total sampling frame, so data are expanded. With the percentage distributions of response variables, we proceed to weigh the same setting for this five weights:
Each response rate is multiplied by the weighting assigned, then joined data weighted for each option and generates the indicator for each component (variable), and finally, it takes a simple average.
The indicators are designed so that its values fluctuate between 0 and 100. As the views show some relative improvement in the situation will widespread, the indicator value is concerned increases. In other words, as optimism is widespread among respondents, the value of indicator increases. Similarly, as the percentage of respondents with pessimistic views increases, the indicator value will decrease. Thus, when growing or qualitative indicator decreases, this reflects a greater likelihood that quantitative indicator concerned (production, employed personnel, etc.), if available, also show a similar trend. In this sense, it is important that indicators such as the IAT and its components serve identifying potential trends but not to establish point forecasts of the rates of change hard indicators from other sources.
Often in this type of indicator uses the value of 50 as the threshold to separate optimism pessimism. However, it is important to recognize that the interpretation is somewhat more complicated in the very likely event that at least one informant answer has been optimistic and pessimistic. If so, consider the value of 50 as the threshold between pessimism and optimism and not as correct since it involves the aggregation subjective assessments that place responses within a structure that is ordinal but not cardinal. Put another way, since we do not have elements to objectively measure the emotional intensity of each review would require recourse to assumptions extremely unrealistic to add subjective opinions. This means that the real threshold cannot be just 50, but any value in this environment figure. In fact, it is common in cases with sufficiently long series, the identification of threshold is made on an econometric from seasonally adjusted, by association diffusion indicator of the economy hard numbers. Such is the case, for example, the Managers' Index Buy from the U.S., for which we have identified a threshold of 47.0, even if the range of questions varies between zero and one hundred, focusing on fifty. In this sense, is presented to the user is limitation of the data and take into account suggests to analyze the results.
At the source: