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Effects of a Tax Reform: Increase in Value-Added Tax in Ecuador as a

Post-Catastrophe Economic Measure

Guido Macas-Acosta*

Génesis Macas-Lituma**

Arnaldo Vergara-Romero***

ABSTRACT

This study delves into the direct impact of a 2% increase in Value Added Tax (VAT) on

firms' sales in Ecuador. Employing a quasi-experimental design and canton-level data (224)

for the period 2014-2017, we compare the sales of localities affected by the tax reform

(

treatment group) with those that were not (control group). By utilizing a difference-in-

differences analysis, we were able to isolate the specific effect of the VAT increase,

minimizing the impact of other factors that may have influenced sales during that period.

The results reveal a negative and statistically significant causal relationship between the

VAT hike and firms' sales. In other words, the increase in the tax led to a contraction in the

demand for goods and services, resulting in a decline in firms' revenue. These findings

suggest that increases in consumption taxes can adversely affect economic activity by

discouraging consumption and negatively impacting firms' competitiveness. The results of

this research hold significant implications for the formulation of fiscal policy, as they

highlight the need to carefully evaluate the potential side effects of changes in tax rates on

consumer and firm behavior.

KEYWORDS: Fiscal policy, Taxation, Income distribution, Income policy, Ecuador.

*

Universidad Ecotec. Associate Professor, Ecuador. ORCID:https://orcid.org/0000-0003-4710-7422.

E-mail: gmacas@ecotec.edu.ec

*

*B.S. in Economics, Universidad Ecotec, Graduated. Samborondón, Ecuador. E-mail:

gmacas@est.ecotec.edu.ec

*

**Universidad Ecotec. MSc. in Economics, Universidad Ecotec, Associate Professor, Research

Departments, Ecuador. ORCID: https://orcid.org/0000-0001-8503-3685. E-mail:

avergarar@ecotec.edu.ec

Recibido: 15/04/2024

Aceptado: 11/06/2024

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Efectos de una Reforma Tributaria: Aumento del Impuesto al Valor

Agregado en Ecuador como medida económica posterior a una catástrofe

RESUMEN

Este estudio emprende un análisis exhaustivo del impacto directo que tuvo un aumento del

2

% en el Impuesto sobre el Valor Añadido (IVA) sobre las ventas de las empresas en

Ecuador. Utilizando un diseño cuasi-experimental y datos a nivel cantonal (224) para el

período 2014-2017, se compararon las ventas de las localidades que experimentaron este

incremento tributario (grupo de tratamiento) con aquellas que no se vieron afectadas

(

grupo de control). A través de un análisis de diferencias en diferencias, se logró aislar el

efecto específico del aumento del IVA, minimizando el impacto de otros factores que

pudieran haber influido en las ventas durante ese período. Los resultados obtenidos revelan

una relación causal negativa y estadísticamente significativa entre el incremento del IVA y

las ventas de las empresas. En otras palabras, el aumento del impuesto generó una

contracción en la demanda de bienes y servicios, lo que se tradujo en una reducción de los

ingresos para las empresas. Estos hallazgos sugieren que los aumentos en los impuestos al

consumo pueden tener efectos adversos sobre la actividad económica, al desincentivar el

consumo y afectar negativamente la competitividad de las empresas. Los resultados de esta

investigación tienen importantes implicaciones para la formulación de políticas fiscales,

pues resaltan la necesidad de evaluar cuidadosamente los potenciales efectos colaterales de

los cambios en las tasas impositivas sobre el comportamiento de los consumidores y las

empresas.

PALABRAS CLAVE: Política fiscal, Tributación, Distribución del ingreso, Política de

ingresos, Ecuador.

Introduction

The effects of tax reforms on economic activity have been under debate for a long time,

allowing for a vast amount of academic literature. Many bets on macro-econometric

estimation methods have led to maintaining standard ideas. Taxes introduce massive

distortions that lead to less economic development (Infantino, 2020), or fiscal policy

remains the main macroeconomic policy lever to counter adverse economic shocks and

possibly foster economic growth (van der Wielen, 2019).

In other studies, emphasis has been placed on the fact that the best responsible fiscal

policy management should prevail. Creating a climate that encourages the private sector to

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make medium- and long-term decisions with greater confidence will improve economic

productivity, which is vital for long-term growth (Segura, 2015).

This article aims to extend the existing set of estimates of the effects using methods that

allow evaluation of the impact of public policies. This document seeks to quantify the

development of the increase of two percentage points in VAT on sales between June 2016

and May 2017.

Undoubtedly, this type of evaluation will prove the effectiveness of a specific program or

public policy. Impact evaluations are necessary to inform those responsible for improving

policies and taking corrective action on their intervention objectives (Gertler et al., 2017).

Taxes and their effects on the economy have relevant relationships in the market and the

behavior of its main variables, such as income, GDP, consumption, investment, and revenue.

Applying a new tax can generate positive or negative economic impacts, even when other

factors such as public spending, social benefits, incentives, and trade policy measures are

incorporated.

The classical and neoclassical position defends a position on impacts. Adam Smith, in his

book "Inquiry into the Nature and Causes of the Wealth of Nations", Adam Smith laid the

foundation that raising (imposing) tax rates beyond a certain level discouraged compliance,

encouraged smuggling, and reduced tax revenue (Hedau, 2018). Hedau (2018) mentions

that taxes should be designed to minimize taxpayer compliance and government

administrative costs while discouraging tax avoidance and evasion.

The neoclassical view holds that income and wealth must first be produced and then

consumed, which means that taxes on factors of production, such as capital and labor, are

particularly detrimental to wealth creation. Corporate and shareholder taxes reduce the

incentive to invest and build capital (McBride, 2012).

In the empirical field, a series of studies try to explain the impacts on the market. The

main contributions focused on developing theories that explain the incidence of general

sales taxes and taxes on certain goods. Most research has focused on the incidence theory of

the tax, and the legal conclusion of much of this theoretical analysis is that consumers bear

the entire burden of any sales and excise tax (Alm et al., 2009).

The main contributions were from Brown (1939), Rolph (1952), and Bishop (1968).

However, with more sophisticated statistical and econometric tools, software, and

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techniques, empirical evidence and impact assessments of the measures in each economic

and social variable were expanding.

The results vary according to the countries, the methodologies, the fiscal variables

involved, and the periods within the same country. The studies distinguish between the

types of taxes, from corporate income taxes, personal income taxes, consumption taxes

through Value Added Tax (VAT), and property taxes.

The studies range from a province, region, country, economic sector, and product. That is

the case of Blagrave (2005), who analyzes the impact of the harmonized sales tax on

provincial revenues in the Atlantic Canada area. Their methodological strategy focused on

an OLS regression to predict the relationship between the forecast variable (consumption

tax revenue) and explanatory variables such as provincial GDP and disposable personal

income in the three participating provinces. These provinces had the highest sales tax rates

in the country, and the proposal to lower those high tax rates to eight percent (along with

changing the tax bases) ended up benefiting consumers (Blagrave, 2005).

Another line of research uses vector auto regression (VARs) to measure tax multipliers.

The idea is to include shocks to taxes and government revenue in a VAR (Romer & Romer,

2

010). According to the researchers, if they are orthogonal to the relevant information

established in the VAR, then the fiscal multipliers are calculated naturally through the

impulse responses to such shocks generated by the VAR (Favero & Giavazzi, 2012) in their

research on the " Measuring Tax Multipliers: The VAR Method", argues that using this

approach solves an apparent puzzle in measuring tax multipliers.

In their research, Romer & Romer (2010) and Barro & Redlick (2011) found substantial

effects of tax changes on economic activity. The first estimate is that the impact of a 1

percent GDP tax increase is equivalent to a 3 percent reduction in output over three years.

David and Christina Romer, in their research, look at the overall U.S. federal tax burden as a

percentage of GDP since World War II. Analyze the record of federal tax changes,

including presidential speeches and congressional reports, to identify legislated "fiscal

shocks," such as attempts to reduce a budget deficit or promote long-term growth (Romer

&

Romer, 2010).

The most significant effect comes from tax changes to promote economic growth, and

the main channel is investment. These results are robust for several specifications,

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including controlling for the state of the economy, monetary policy, and public spending

behavior (McBride, 2012).

Moreover, Barro and Redlick point out that taxes' effect on GDP works mainly through

substitution effects, with increases in average marginal tax rates considerably reducing

GDP (Barro & Redlick, 2011).

Blanchard and Perotti (2002) point out that positive fiscal shocks, such as unexpected

increases in total revenue, negatively affect private investment and GDP.

For William Gale (2014), in his research "Effects of changes in income tax on economic

growth", the critical advantage of the approach is that it allows a distinction between

anticipated and unanticipated fiscal shocks based on temporary assumptions. In addition,

and at least partially, control for available information on future tax changes is usually

ignored in standard VAR-based methods (Gale & Samwick, 2014).

The general equilibrium model with tax that includes the participation of families,

companies, and the Government follows the same research path, seeking the best strategy

to estimate the impact of fiscal policy shocks. The Dynamic General Equilibrium Model

(

Conesa et al., 2010) was applied to the Spanish economy.

For other researchers, increasing corporate taxes is the most damaging, followed by

personal income, consumption, and property taxes. In the research "Tax Policy For

Economic Recovery and Growth” by Arnold et al. (2011), where the behavior of tax reforms

and their effects between 1971 and 2004 are analyzed in 21 OECD countries, it is pointed

out that the progressivity of income taxes damages growth A 1 percent shift in tax revenue

from income tax (both personal and corporate) to consumption and property taxes would

increase GDP per capita by 0.25 to 1 percent over the long run term Corporate taxes, both

in terms of the statutory rate and depreciation deductions, reduce investment and

productivity growth Raising the top marginal rate on personal income reduces productivity

growth (Arnold et al., 2011).

Van der Wielen explained that the estimates made for the EU are based on a structural

identification of fiscal shocks (Burriel et al., 2010); they focus on public spending shocks

(

Mencinger, 2017) or measures cyclically adjusted budgets (Carnot & de Castro, 2015;

Gechert et al., 2019).

Several recent contributions reveal that increasing taxes affect income and salaries. To

do this, they have developed more sophisticated general equilibrium models of the long-

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term incidence of corporate income taxes in an open economy, as described by Randolph

(

2006) and Gravelle & Thomas (2011).

Most empirical studies on taxes and their effects on the variables that promote economic

growth, published in peer-reviewed academic journals, find that tax increases hurt the

economy.

Moreover, in a review of twenty-six such studies since 1983, at least three found no

negative effect of taxes on growth. The rest found a generation of problems in the

macroeconomic variables.

For García (2011), the causal analysis based on structural equations has many criticisms

and is based on deficiencies in reproducing the observed data (García, 2011). Lalonde (1986)

commented that empirically, the structural models based on regressions give poor results

compared to more experimental methods.

For this reason, the difference-in-difference method (DID) will be designed, in which the

sales of the taxpaying companies are compared before and after the implementation of

raising the VAT from 12 to 14%, which will include the provinces that received the increase.

Moreover, those that remained with the same tax.

-

What happened in Ecuador?

At the beginning of 2016, the Ecuadorian economy faced a reduction in its Gross

Domestic Product (GDP) growth rates. According to the Central Bank of Ecuador (BCE),

the first quarter of 2016 registered a decrease in GDP of 4%, and the fourth quarter of 2015

reported a decline of 2% (BCE, 2017). In this context, former President Rafael Correa

presented the Organic Law for the Balance of Public Finances, which aims to boost

domestic consumption and production.

The project was sent to the National Assembly as an urgent economic issue on March 30,

2

016. The first debate on the bill was on April 11, and five days later, an earthquake (7.8

magnitudes) destroyed the productive sectors of the provinces of Manabí and Esmeraldas.

Official figures record 671 people dead and 8,690 people sheltered. In addition, it affected

the provinces of Esmeraldas, Guayas, Los Ríos, Santa Domingo, and Santa Elena. Thus, on

April 17, 2016, the President of the Republic, Rafael Correa, issued Decree 1001, declaring a

State of exception for sixty days to the Esmeraldas, Manabí, Santa Elena provinces, Los

Ríos, Santo Domingo, and Guayas just as it orders the Ministry of Finance to allocate the

funds to meet the needs caused by the earthquake.

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A few days later, the government issued decree 1002, which extended the mobilization to

the entire country and provided for the requisitions for which there was room to solve the

emergency.

Likewise, between April 17 and 20, former President Correa and his work team prepared

another economic project called the Solidarity and Citizen Co-responsibility Law for the

Reconstruction and Reactivation of the Areas Affected by the Earthquake, which will serve

to finance the rehabilitation and reconstruction of the areas affected by the earthquake.

The original proposal included an increase of 2 in VAT, an additional 3% contribution

from companies on profits, a 0.9% contribution from people with assets greater than 1

million dollars, the gift of one day's salary of those who earn more than 1,000 and the sale of

public support.

The proposal for the Solidarity Law was sent to the National Assembly on April 20 as an

urgent economic matter.

On April 26, decree 1004 was issued to create the Reconstruction and Productive

Reactivation Committee in the affected areas. Its functions are to implement programs,

plans, actions, and public policies to reactivate production and employment in the area.

Former Vice President Jorge Glass presided over the committee, and he worked with

several State Ministers in executing the Reconstruction Plan.

On that same day, the Assembly discussed the Public Finance Balance Bill and approved

it in a second debate. Therefore, April 29 is issued in the Official Gazette, and its articles

focus on the return of two percentage points of the Value Added Tax for using electronic

means of payment when paid with electronic money and 1 point when they used debit,

credit, or prepaid cards. In addition, the return of VAT paid by people with disabilities or

by older adults on a taxable base of up to two unified basic salaries.

Also included is the exemption in the payment of income tax for older adults (one basic

fraction exempt) and people with disabilities or their only substitute two basic fractions

exempt). Moreover, the advance payment of Income Tax for micro-enterprises is reduced

through a simplified calculation.

Furthermore, a taxable base for the Special Consumption Tax is established for alcoholic

and non-alcoholic beverages. Moreover, a 15% special consumption tax rate has been

restored for companies with fixed and mobile telephones, excluding internet and data

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services. An additional 50% IR deduction is also established for Excise Tax (ICE) payments

generated in telephone services for centralized call management offices (call centers).

The first debate of the Solidarity Law was held on May 3, 2016, and its second debate

was approved on May 12. Furthermore, it was published in the Official Gazette for

execution on May 20. However, it was not until June 10 that Decree 1073 approved the

Regulations of the Solidarity Law.

The Solidarity Law, in Article 1, indicated that its objective is the collection of solidarity

contributions to allow the planning, construction, and reconstruction of public and private

infrastructure and productive reactivation. Article 2 maintained that the following

solidarity contributions are created only once: on remunerations, heritage, profits, and real

estate and capital rights in Ecuador owned by companies resident in tax havens or other

foreign jurisdictions.

In addition, it includes the contribution to real estate and rights representing capital

existing in Ecuador and a 0.9% contribution on the inheritance of natural persons equal to

or greater than one million dollars. Moreover, finally, one day of their remuneration of

natural persons in a relationship of dependency who receive more than 1000 dollars per

month and the temporary increase of 12% of VAT for one year.

Furthermore, the first Transitory Provision provides for an increase from 12 to 14% for

one year. In addition, it provides that natural persons who are final consumers and

purchase goods or services in the provinces of Manabí and Esmeraldas will receive from the

State a discount equivalent to the increase of two percentage points of the VAT paid on

their consumption. That is, the tax will not be increased in those localities.

On May 25, 2016, Decree 1044 was issued, which provides for the exemption from the

payment of 100% of the advance value of Income Tax for the 2016 fiscal period to all

economic sectors of the cantons of Manabí such as Bolívar, Chone, El Carmen, Flavio Alfaro,

Jama, Jaramijó, Junín, Manta, Montecristi, Pedernales, Pichincha, Portoviejo, Rocafuerte,

San Vicente, Santa Ana, Sucre, and Tosagua. In addition, it is located in the Muisne canton

of the province of Esmeraldas.

On May 31, 2016, representatives of ECLAC, the United Nations, and Secretaria Nacional

de Planificación y Desarrollo (SENPLADES) presented the reconstruction costs of the

provinces of Manabí and Esmeraldas, which were affected by the earthquake. According to

the Reconstruction Costs Evaluation report, the total cost for the reconstruction of the

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affected areas amounts to 3,343.8 million dollars, of which 2,252.3 million (67%) would

come from the public sector and 1,091.5 million (33%) from the private sector (SENPLADES,

2

016).

1

. Materials and Methods

The empirical analysis of this article is based on the sales collections by cantons obtained

on the Internal Revenue Service (SRI) website in the multidimensional statistics section,

which is responsible for providing information on form 104

https://declaraciones.sri.gob.ec/saiku-ui/). There, the declarations of the commercialized

(

goods' taxes with VAT 0% and VAT 12% by province and cantons are registered. The same

ones will be selected from the period 2014 to May 2017. There are 224 cantons distributed

in 24 regions of Ecuador that report the amounts sold are counted. The population of each

canton will also be used to build a per capita sales indicator for each city.

May 2016 is used to analyze the treatment period, while the pre-treatment period goes

from January 2014 to April 2016. The post-treatment period goes from June 2016 to May

2

017. Therefore, each analysis period has 28 and 12 months.

It must be remembered that the information does not come from a random assignment

when evaluating the impact. Work is done on existing databases and can be considered

quasi-experimental. In addition, we use the information by canton where the affected areas

are classified (the cantons of Esmeraldas and Manabí), in which the VAT increase measures

from 12 to 14% are not applied and which will be considered control groups. The rest of the

cities will make up the treatment group.

It is important to remember that in May 2016, the Solidarity Law was approved, which

increases VAT from 12 to 14% in 22 of the 24 provinces. The tax for necessities throughout

the country has remained the same. Sales that do not have VAT (0%) and are applied

throughout the country will also be used, especially for necessities that are part of the basic

basket.

The supporting data and forms, such as revenue behavior, collections, tax payments, and

more details about economic activity and geographic location, are all publicly available.

1

.1. Empirical Model

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Understanding and outlining the mechanisms by which the VAT increase can affect sales

is necessary to estimate the causal relationship between fiscal policy and the demand for

goods.

The difference-in-differences technique will be used to estimate the impact of the two-

percentage-point increase in VAT on sales. This quasi-experimental design uses

longitudinal data from the treatment and control groups to obtain an appropriate

counterfactual for estimating a causal effect (Imbens & Wooldridge, 2009).

This method was used in many economic and social evaluation studies. One of the best-

known was to estimate the impact of the New Jersey minimum wage increase on

employment in fast food restaurants in New Jersey and Pennsylvania (Card & Krueger,

1

994; Vergara-Romero et al., 2022). Another study investigated how the evolution of a tax

subsidy to employer-provided health insurance affects employer-provided health insurance

coverage (Finkelstein, 2002). The difference-in-difference methodology is also used to

assess the effect of the terrorist conflict on the economic evolution of the Basque Country

using Spanish regions not affected by the conflict as a synthetic control group (Abadie &

Gardeazabal, 2003). These studies show that the DID method can control for effects due to

general time trends, regional differences, and other confounding factors. However, this

method has yet to be used in any analysis of tax reforms.

However, one of the criticisms of this method is the issue of parallel trends where

evidence is required to confirm that assumption. Moreover, you must know that similar

groups only sometimes exhibit truly parallel trends. Moreover, this can be generated

because the control group is not very good or because the functional form of the

counterfactual is incorrect. Using a fictitious or falsified trend test, researchers must test

the assumption of parallel trends whenever the data allows (Kahn-Lang & Lang, 2019).

The basic proposal is that observations are collected for two groups during two periods.

One of the groups is the treatment group that is exposed to the treatment in one period.

The other group, the control group, receives no treatment during both periods. If the same

units are observed within a group at each period, the average gain in the unexposed

(

control) group is subtracted from the gain over time in the exposed (treatment) group.

This double differentiation, also called the “difference-in-difference” method, seeks to

eliminate biases in the second-period comparison between treatment and control groups

that could be the result of permanent differences between those groups, as well as

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comparison biases in time in the treatment group, which could be the result of non-

treatment related time trends (Li et al., 2012).

This technique estimates the effect of a specific public policy or treatment by comparing

changes in outcomes over time between a measure applied to a group of study units (the

intervention group) and a group of study units that it is not, called a control group.

This difference-in-difference design (DID) will seek to compare sales before and after the

implementation of raising VAT from 12% to 14% for the cantons unaffected by the

earthquake, regardless of the number of inhabitants since other factors that change over

time can affect sales and confuse a simple before and after policy comparison. The spurious

effect due to secular trends will be removed using a DID model (Donald & Lang, 2007). The

DID method is based on identifying a control group that (1) does not have a VAT increase

and (2) experiences the same or parallel secular trends in sales of products with and

without VAT (see Figure 1).

Figure 1. The trends of sales of treatment (VAT 14%) and control (VAT 12%).

The effect of VAT on sales was estimated as the difference between the change in income

before and after the introduction of the tax increase in the treatment group (i.e., the actual

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effect of VAT) and the change in income before and after VAT with no increase in the

control group (i.e., only secular trends in outcome).

The DID estimate is unbiased when trends in canton sales due to unobserved factors in

the control group are the same as they would have been in the treatment-eligible group if

the eligible group had not been exposed. to politics (Angrist & Pischke, 2009). The control

group should ideally be like the qualified group, except for the eligibility characteristics.

The parallel prior trends test arises naturally in the potential treatment approach to DiD,

which assumes we can write possible outcomes for a group (Macas-Acosta et al., 2022).

To correct this, a DD could be estimated for the affected group (sales with VAT) and a

DD for the non-affected group (sales without VAT). The triple difference estimator (DDD)

is then calculated as the difference in the DD estimators comprising the interaction of the

multiplication of the dummy variables (iva*after*tax). With this situation, the assumption

of identification changes since now the difference in the change in the time between the

treated and control groups that correspond to the sales that pay VAT is a good

counterfactual of the difference in the change in the time between the group treaty and rule

that fits sales that do NOT pay VAT (see figure 2).

Figure 2. The trends of sales of treatment (VAT 0%) and control (VAT 0%).

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This way, possible results could be found, and various specifications could be applied as

double differences but with control variables such as time, province, trend, and then triple

difference. In addition, there is a double contrast between goods that pay and do not pay

VAT only in cantons outside of Esmeraldas and Manabí. Thus, it is also determined its

robustness to these specifications.

1

.2. Variables

The event is the VAT increase from 12 to 14% that was applied in May 2016, but only to

the cantons of the provinces unaffected by the earthquake, which became the treatment.

The cantons of the two regions affected by the quake will not increase so that they will be

under control.

Sales without VAT remain the same in all country cantons since they are essential

products. The study focuses on a single period (cross-section).

The following variables are identified in the investigation:

Per capita sales in dollars that are made with the Value Added Tax (VAT) of 12%

Per capita sales in dollars that are made with the Value Added Tax (VAT) of 14%

The per capita sales in dollars made without the Value Added Tax (VAT) is 0%.

A dummy variable to identify the event of the application of the VAT increase from

1

2 to 14%

Generate a temporary variable for the panel: gen month_year = ym(year, month)

Generate a variable ID Panel: gen canton_prov = province*1000+canton

Generate a post VAT increase: gen after = month_year>tm(2016may)

Generate a binary variable: 1 if VAT increased in a non-affected province and 0 only

for Esmeraldas and Manabí: gen tax = 1

Generate a logarithm of sales per capita: lsales = log(sales)

In addition, create an Interaction between the generated variables:

gen ddd = vat*after*tax

gene d1 = after*tax

gen d2 = vat*after

gen d3 = vat*tax

Generate a leading indicator of taxes (leading indicators - tax)

gen month1 = month_year17*tax

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gen month2 = month_year16*tax

Generate a leading indicator of VAT (leading indicators - VAT)

gen month1 = month_year17*vat

gen month2 = month_year16*vat

Generate a trend variable by province: tab province, gen(prov)

The potential problems that can be identified could be generated if people who live in

nearby cantons and who have the VAT increase can move to a city that does not have the

measure.

1

.3. Empirical Model

This section explains the methodology used to verify the hypothesis that the VAT

increase impacts sales. In the first instance, three equations were structured, each with four

models that will allow for the best strategy to determine the most efficient and consistent

coefficients. The first equation tries to analyze a difference between the control (Manabí

and Esmeraldas) vs. the treatment (rest of the country) on the VAT increase but in different

models starting with effects of time, province, and trend with the province. The objective is

to obtain the coefficient d1.

ꢀ

ꢁꢂꢀꢃꢁ = ꢆ + ꢇ ꢂꢈꢅꢃꢉ + ꢇ ꢅꢂꢊ + ꢇ ꢋ + ꢌ (1)

ꢄꢅ 1 ꢄꢅ 2 ꢄꢅ 3 1 ꢄꢅ

The second equation tries to analyze a difference between the control (Manabí and

Esmeraldas) and the treatment (rest of the country) on those who pay the VAT and those

who pay 0% of the tax but in different models starting with time effects, province, and

trend with the province. The objective is to obtain the coefficient d2. Equation 3 is then

carried out to get the global development of the impact of tax measures globally.

ꢀ

ꢁꢂꢀꢃꢁ = ꢆ + ꢇ ꢍꢎꢏ + ꢇ ꢂꢈꢅꢃꢉ + ꢇ ꢋ + ꢌ (2)

ꢄꢅ 1 ꢄꢅ 2 ꢄꢅ 3 2 ꢄꢅ

ꢀ

ꢁꢂꢀꢃꢁ = ꢆ + ꢇ ꢍꢎꢏ + ꢇ ꢂꢈꢅꢃꢉ + ꢇ ꢅꢂꢊ + ꢇ ꢋ + ꢇ ꢋ + ꢇ ꢋ + ꢇ ꢋꢋꢋ + ꢌ

ꢄꢅ 1 2 3 ꢄꢅ 4 1 2 6 3

ꢄꢅ ꢄꢅ 5 7 ꢄꢅ

(

3)

4

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Then, models are made to verify that the trends are parallel before the fiscal measure. The

idea is to demonstrate no effect on products that do not pay the VAT with the three

additional specifications: time effects, province effects, and effects in conjunction with

trend and province.

ꢀ

ꢁꢂꢀꢃꢁ = ꢆ + ꢇ ꢂꢈꢅꢃꢉ + ꢇ ꢅꢂꢊ + ꢇ ꢋ + ꢌ

ꢄꢅ

ꢄꢈ ꢍꢎꢏ == 0

(4)

(5)

ꢄꢅ

1

ꢄꢅ

2

ꢄꢅ

3

1

ꢀ

ꢁꢂꢀꢃꢁ = ꢆ + ꢇ ꢍꢎꢏ + ꢇ ꢂꢈꢅꢃꢉ + ꢇ ꢋ + ꢌ

ꢄꢅ

1

ꢄꢅ

2

ꢄꢅ

3

2

This strategy is critical because it may happen that the control group is not very good or

because the functional form of the counterfactual is incorrect. Therefore, whenever the data

allows, researchers must test the assumption of parallel trends using a "dummy trend" test

(

Kahn-Lang & Lang, 2019).

Angrist and Pischke (2010) argued that the more effective differences-in-differences

method reports the results of treatment and control observations over a period long enough

to show underlying trends, with attention focused on how deviations of the direction are

related to changes in policy (Angrist & Pischke, 2010; Romero-Subia et al., 2022).

2. Results

With the defined variables and the transformed data, it was possible to carry out the

first regression (equation 1), but with different control variables where its results are

demonstrated in four models. The purpose was to determine the coefficients of the variable

d1, which is the interaction of the variables after tax. That is, obtain the first difference

between the effect when the VAT increase was generated between the treatment and

control groups. The best result was the fourth model since it has all the control variables,

and its coefficient was negative, -0.2544, and significant (See Table 1).

The second equation has the same structure as the previous one, but now the variables

VAT, after, and d2 are included. Seeing the difference between those who pay the new VAT

and those who remain with the 0% VAT is a matter of seeing it. Likewise, four models were

carried out; the last one generated a negative coefficient of -0.1315, which is also significant.

The difference with the rest of the models is similar since the first obtained -0.1383 but

without the corresponding effects.

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With the two equations measuring the difference at different times, the third equation

can now be executed. Its main objective is to obtain the coefficient of the third difference

(

D), which quantifies the impact of the VAT increase in the 12 months that the measure

lasted.

Table 2 shows that the coefficient of the id variable is the same and highly significant in

the four models. This implies that the increase of two percentage points caused a reduction

in the average per capita sales transformed into logarithms of approximately 22.3% in that

period.

Table 1. Primary Outcomes VAT 0%, 12%, and 14%.

VAT 12% vs. VAT 14%

MODEL 1

MODEL 2

0.3198***

(0.0282)

1.3638**

(0.6581)

-0.2463***

(0.0294)

YES

MODEL 3

0.3224***

(0.0279)

1.3638**

(0.6572)

-0.2492***

(0.0291)

YES

MODEL 4

0.3257***

(0.0286)

1.4192**

(0.5860)

-0.2544***

(0.0293)

YES

After

0.1637***

(

0.0268)

1.3635**

0.6572)

-0.2460***

Tax

d1

(

(0.0294)

Time effect

NO

Province effect

Trend and province

VAT 14% vs. VAT 0%

VAT

NO

YES

NO

YES

MODEL 1

MODEL 2

0.7067***

(0.1762)

0.2066***

(0.0237)

-0.1383***

(0.0141)

YES

MODEL 3

0.6998***

(0.1765)

0.2032***

(0.0236)

-0.1315***

(0.0142)

YES

MODEL 4

0.6998***

(0.1766)

0.2021***

(0.0231)

-0.1315***

(0.0142)

YES

0.7067***

(

0.1761)

0.0560***

0.0201)

-0.1383***

After

d2

(

0.0141)

Time effect

NO

Province effect

Trend and province

NO

YES

NO

YES

Source: Authors’ Compilation.

This reduction was generated only for taxpayers in the cantons that suffered the measure.

In certain cities, the values were higher because there was more movement, and their

inhabitants could not access the same goods they used to consume.

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Superficial differences certainly provide an unbiased estimate of treatment effects.

However, for these coefficients to be potentially robust, they must be verified using a

falsification test. Different models will be applied to demonstrate no impact on products

that do not pay the VAT with all the controls, both for the selected group as treatment and

management.

Table 3 shows that after May 2016, sales of products with zero tax (staple foods)

increased by 24.38 in the cities considered as treatment. Furthermore, if the control cities

are also analyzed, they also had increases in sales of 29.9%; both coefficients came out

significant in the regression that all possible controls were used.

Table 2. Secondary Outcomes Difference in Difference.

MODEL 1

MODEL 2

0.1526

MODEL 3

0.1451

MODEL 4

0.1451

VAT

After

Tax

d1

0.1526

(

0.1562)

0.0790**

0.0255)

0.8094

(0.1563)

0.2391***

(0.0264)

0.8997

(0.1564)

0.2359***

(0.0261)

0.8103

(0.1563)

0.2387***

(0.0264)

0.8167

(

(0.4870)

(0.4873)

-0.0232

(0.0325)

0.0846**

(0.0315)

0.5541**

(0.2355)

-0.2230***

(0.0345)

YES

(0.4869)

-0.0238

(0.0319)

0.0921**

(0.0316)

0.5541**

(0.2355)

-0.2230***

(0.0346)

YES

(0.5722)

0.0279

-0.0238

(0.0268)

(0.0314)

0.0921**

(0.0316)

0.5541**

(0.2357)

-0.2230***

(0.0346)

YES

d2

0.0846**

(

0.0315)

0.5541**

0.0294)

-0.2230***

d3

(

ddd

(0.0345)

Time effect

NO

Province effect

Trend and province

NO

YES

NO

YES

Source: Authors’ Compilation.

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Table 3. 0% VAT in Treatment Provinces

VAT 0% (Rest of the country)

MODEL 1

MODEL 2

0.2431***

MODEL 3

0.2416***

MODEL 4

0.2438***

After

0.0790**

(

0.0255)

(0.0305)

0.8097

(0.4876)

-0.0231

(0.0325)

YES

(0.0305)

0.8079

(0.4863)

-0.0214

(0.0320)

YES

(0.0308)

0.7584

(0.5802)

-0.0245

(0.0315)

YES

Tax

d1

0.8094

(0.4870)

-0.0229

(

0.0325)

Time effect

NO

Province effect

Trend and province

NO

YES

NO

YES

VAT 0% (Esmeraldas

&

MODEL 1 MODEL 2

MODEL 3

MODEL 4

Manabí)

VAT

0.1526

(0.1594)

0.3040***

(0.0270)

0.0846**

(0.0321)

YES

0.141

(0.1594)

0.2982***

(0.0267)

0.0962**

(0.0328)

YES

0.141

(0.1594)

0.2990***

(0.0269)

0.0962**

(0.0328)

YES

(0.1586)

After

d2

0.0790**

0.0259)

0.0846**

(

0.0320)

Time effect

NO

Province effect

Trend and province

NO

YES

NO

YES

Source: Authors’ Compilation.

Conclusions

Most governments frequently use tax reforms to access liquidity and finance their

current expenses, social programs, or reconstruction. In this sense, it is essential to quantify

its effects. A better understanding of these effects can benefit public policymakers and

academics interested in studying fiscal policy empirically. This research contributes to the

literature by applying a method that allows estimating the causal relationship effect of a

specific tax policy on commercial transactions on their sales income.

This research studies the impact of the value-added tax (VAT) increase from 12 to 14%

imposed by the Ecuadorian government in May 2016 and last year to finance the damage

caused by the earthquake in April 2016. The analysis was focused on the sales of products

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taxed with VAT and those that do not have a tax (0% VAT). We use a differences-in-

differences approach to obtain an unbiased estimate, which creates an appropriate control

by combining product sales information in two provinces unaffected by the policy change.

The results indicate that the two-percentage point increase produced a statistically

significant reduction in sales in 22 provinces of 22.3%. Interestingly, this estimate is very

similar to a before and after assessment. It can be seen as evidence that the policy shock

under investigation did not co-occur with other relevant but unobserved (by the researcher)

or that it is exogenous. The exogeneity and the apparent stationarity of the series imply

that a before and after comparison provides a reasonable estimate of the treatment effect.

In this sense, this research's main contribution is methodological. The differences-in-

differences method can be used as a robustness check for more formal specifications and as

an indirect test for the homogeneity of policy shocks. Furthermore, if the policy under

study coincides with, and is therefore confounded with, other changes observed nationally

or internationally, other methods could be combined to estimate the causal effect of interest.

Finally, the estimation method used has the potential to assess the impact of particular

policies or programs on outcome variables other than business sales, such as taxes collected,

investment flows, assistance programs, and job creation, among others.

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Conflicto de interés

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Declaración ética

Los autores declaran que el proceso de investigación que dio lugar al presente manuscrito se desarrolló

siguiendo criterios éticos, por lo que fueron empleadas en forma racional y profesional las herramientas

tecnológicas asociadas a la generación del conocimiento.

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